{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5d9e5a5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "8de0debf",
   "metadata": {},
   "outputs": [],
   "source": [
    "fandango = pd.read_csv(r\"C:\\Users\\Teni\\Desktop\\Git-Github\\06-Capstone-Project\\fandango_scrape.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9164c9d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Valiyavan (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>WWE SummerSlam 2015 (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Yagavarayinum Naa Kaakka (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Yesterday, Today and Tomorrow (1964)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Zarafa (2012)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     FILM  STARS  RATING  VOTES\n",
       "0             Fifty Shades of Grey (2015)    4.0     3.9  34846\n",
       "1                   Jurassic World (2015)    4.5     4.5  34390\n",
       "2                  American Sniper (2015)    5.0     4.8  34085\n",
       "3                        Furious 7 (2015)    5.0     4.8  33538\n",
       "4                       Inside Out (2015)    4.5     4.5  15749\n",
       "..                                    ...    ...     ...    ...\n",
       "499                      Valiyavan (2015)    0.0     0.0      0\n",
       "500            WWE SummerSlam 2015 (2015)    0.0     0.0      0\n",
       "501       Yagavarayinum Naa Kaakka (2015)    0.0     0.0      0\n",
       "502  Yesterday, Today and Tomorrow (1964)    0.0     0.0      0\n",
       "503                         Zarafa (2012)    0.0     0.0      0\n",
       "\n",
       "[504 rows x 4 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "042d1d44",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Understand the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1a805b9f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 504 entries, 0 to 503\n",
      "Data columns (total 4 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   FILM    504 non-null    object \n",
      " 1   STARS   504 non-null    float64\n",
      " 2   RATING  504 non-null    float64\n",
      " 3   VOTES   504 non-null    int64  \n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 15.9+ KB\n"
     ]
    }
   ],
   "source": [
    "fandango.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "82ec8b17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>504.000000</td>\n",
       "      <td>504.000000</td>\n",
       "      <td>504.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.558532</td>\n",
       "      <td>3.375794</td>\n",
       "      <td>1147.863095</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.563133</td>\n",
       "      <td>1.491223</td>\n",
       "      <td>3830.583136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.500000</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>18.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.500000</td>\n",
       "      <td>4.300000</td>\n",
       "      <td>189.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>34846.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            STARS      RATING         VOTES\n",
       "count  504.000000  504.000000    504.000000\n",
       "mean     3.558532    3.375794   1147.863095\n",
       "std      1.563133    1.491223   3830.583136\n",
       "min      0.000000    0.000000      0.000000\n",
       "25%      3.500000    3.100000      3.000000\n",
       "50%      4.000000    3.800000     18.500000\n",
       "75%      4.500000    4.300000    189.750000\n",
       "max      5.000000    5.000000  34846.000000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20b7d3aa",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Explore the relationship between the Rating and Votes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "388acb11",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4), dpi=200)\n",
    "\n",
    "sns.scatterplot(data=fandango, x='RATING', y='VOTES');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "674f5162",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Calculating the correlation between the columns. \n",
    "    \n",
    "This helps undersyand how closely knitted each column is to each other"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d0508cae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>STARS</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.994696</td>\n",
       "      <td>0.164218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RATING</th>\n",
       "      <td>0.994696</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.163764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VOTES</th>\n",
       "      <td>0.164218</td>\n",
       "      <td>0.163764</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           STARS    RATING     VOTES\n",
       "STARS   1.000000  0.994696  0.164218\n",
       "RATING  0.994696  1.000000  0.163764\n",
       "VOTES   0.164218  0.163764  1.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "7d98ac3f",
   "metadata": {},
   "outputs": [],
   "source": [
    "fandango['YEAR'] = fandango['FILM'].str.extract(r'\\((\\d+)\\)')\n",
    "\n",
    "# pd.to_datetime(fandango['YEAR'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "aa6f8987",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Valiyavan (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>WWE SummerSlam 2015 (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Yagavarayinum Naa Kaakka (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Yesterday, Today and Tomorrow (1964)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Zarafa (2012)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     FILM  STARS  RATING  VOTES  YEAR\n",
       "0             Fifty Shades of Grey (2015)    4.0     3.9  34846  2015\n",
       "1                   Jurassic World (2015)    4.5     4.5  34390  2015\n",
       "2                  American Sniper (2015)    5.0     4.8  34085  2015\n",
       "3                        Furious 7 (2015)    5.0     4.8  33538  2015\n",
       "4                       Inside Out (2015)    4.5     4.5  15749  2015\n",
       "..                                    ...    ...     ...    ...   ...\n",
       "499                      Valiyavan (2015)    0.0     0.0      0  2015\n",
       "500            WWE SummerSlam 2015 (2015)    0.0     0.0      0  2015\n",
       "501       Yagavarayinum Naa Kaakka (2015)    0.0     0.0      0  2015\n",
       "502  Yesterday, Today and Tomorrow (1964)    0.0     0.0      0  1964\n",
       "503                         Zarafa (2012)    0.0     0.0      0  2012\n",
       "\n",
       "[504 rows x 5 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c6b9b697",
   "metadata": {},
   "outputs": [],
   "source": [
    "# fandango.drop('Numbers_in_brackets', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "ae7f7948",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Valiyavan (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>WWE SummerSlam 2015 (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Yagavarayinum Naa Kaakka (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Yesterday, Today and Tomorrow (1964)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Zarafa (2012)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     FILM  STARS  RATING  VOTES  YEAR\n",
       "0             Fifty Shades of Grey (2015)    4.0     3.9  34846  2015\n",
       "1                   Jurassic World (2015)    4.5     4.5  34390  2015\n",
       "2                  American Sniper (2015)    5.0     4.8  34085  2015\n",
       "3                        Furious 7 (2015)    5.0     4.8  33538  2015\n",
       "4                       Inside Out (2015)    4.5     4.5  15749  2015\n",
       "..                                    ...    ...     ...    ...   ...\n",
       "499                      Valiyavan (2015)    0.0     0.0      0  2015\n",
       "500            WWE SummerSlam 2015 (2015)    0.0     0.0      0  2015\n",
       "501       Yagavarayinum Naa Kaakka (2015)    0.0     0.0      0  2015\n",
       "502  Yesterday, Today and Tomorrow (1964)    0.0     0.0      0  1964\n",
       "503                         Zarafa (2012)    0.0     0.0      0  2012\n",
       "\n",
       "[504 rows x 5 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69879039",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> How many movies are in the Fandango Dataframe per year?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7fd66491",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2015    477\n",
       "2014     24\n",
       "2016      1\n",
       "1964      1\n",
       "2012      1\n",
       "Name: YEAR, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango['YEAR'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51cc81d8",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> TASK: Visualize the count of movies per year with a plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "72c59359",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Not using the barplot because it'd require a Y variable- which we don't have or do not need. The countlot allows for only counting\n",
    "\n",
    "plt.figure(figsize=(10, 6), dpi=200)\n",
    "sns.countplot(data=fandango, x='YEAR');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9085ac63",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> What are the 10 movies with the highest number of votes?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "d04f92d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Hobbit: The Battle of the Five Armies (2014)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>15337</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kingsman: The Secret Service (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>15205</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Minions (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14998</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>14846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Into the Woods (2014)</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13055</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               FILM  STARS  RATING  VOTES  \\\n",
       "0                       Fifty Shades of Grey (2015)    4.0     3.9  34846   \n",
       "1                             Jurassic World (2015)    4.5     4.5  34390   \n",
       "2                            American Sniper (2015)    5.0     4.8  34085   \n",
       "3                                  Furious 7 (2015)    5.0     4.8  33538   \n",
       "4                                 Inside Out (2015)    4.5     4.5  15749   \n",
       "5  The Hobbit: The Battle of the Five Armies (2014)    4.5     4.3  15337   \n",
       "6               Kingsman: The Secret Service (2015)    4.5     4.2  15205   \n",
       "7                                    Minions (2015)    4.0     4.0  14998   \n",
       "8                    Avengers: Age of Ultron (2015)    5.0     4.5  14846   \n",
       "9                             Into the Woods (2014)    3.5     3.4  13055   \n",
       "\n",
       "   YEAR  \n",
       "0  2015  \n",
       "1  2015  \n",
       "2  2015  \n",
       "3  2015  \n",
       "4  2015  \n",
       "5  2014  \n",
       "6  2015  \n",
       "7  2015  \n",
       "8  2015  \n",
       "9  2014  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango.loc[fandango['VOTES'].nlargest(10).index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "10167356",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Hobbit: The Battle of the Five Armies (2014)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.3</td>\n",
       "      <td>15337</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kingsman: The Secret Service (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>15205</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Minions (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14998</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>14846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Into the Woods (2014)</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>13055</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               FILM  STARS  RATING  VOTES  \\\n",
       "0                       Fifty Shades of Grey (2015)    4.0     3.9  34846   \n",
       "1                             Jurassic World (2015)    4.5     4.5  34390   \n",
       "2                            American Sniper (2015)    5.0     4.8  34085   \n",
       "3                                  Furious 7 (2015)    5.0     4.8  33538   \n",
       "4                                 Inside Out (2015)    4.5     4.5  15749   \n",
       "5  The Hobbit: The Battle of the Five Armies (2014)    4.5     4.3  15337   \n",
       "6               Kingsman: The Secret Service (2015)    4.5     4.2  15205   \n",
       "7                                    Minions (2015)    4.0     4.0  14998   \n",
       "8                    Avengers: Age of Ultron (2015)    5.0     4.5  14846   \n",
       "9                             Into the Woods (2014)    3.5     3.4  13055   \n",
       "\n",
       "   YEAR  \n",
       "0  2015  \n",
       "1  2015  \n",
       "2  2015  \n",
       "3  2015  \n",
       "4  2015  \n",
       "5  2014  \n",
       "6  2015  \n",
       "7  2015  \n",
       "8  2015  \n",
       "9  2014  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# OR\n",
    "fandango.sort_values(by='VOTES', ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a28ef1fa",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> How many movies have zero votes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "b7f27cae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>435</th>\n",
       "      <td>6 Years (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>7 Minutes (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>A Year in Champagne (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>Balls Out (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Before I Wake (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Valiyavan (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>WWE SummerSlam 2015 (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Yagavarayinum Naa Kaakka (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Yesterday, Today and Tomorrow (1964)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Zarafa (2012)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>69 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     FILM  STARS  RATING  VOTES  YEAR\n",
       "435                        6 Years (2015)    0.0     0.0      0  2015\n",
       "436                      7 Minutes (2015)    0.0     0.0      0  2015\n",
       "437            A Year in Champagne (2015)    0.0     0.0      0  2015\n",
       "438                      Balls Out (2015)    0.0     0.0      0  2015\n",
       "439                  Before I Wake (2015)    0.0     0.0      0  2015\n",
       "..                                    ...    ...     ...    ...   ...\n",
       "499                      Valiyavan (2015)    0.0     0.0      0  2015\n",
       "500            WWE SummerSlam 2015 (2015)    0.0     0.0      0  2015\n",
       "501       Yagavarayinum Naa Kaakka (2015)    0.0     0.0      0  2015\n",
       "502  Yesterday, Today and Tomorrow (1964)    0.0     0.0      0  1964\n",
       "503                         Zarafa (2012)    0.0     0.0      0  2012\n",
       "\n",
       "[69 rows x 5 columns]"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango[fandango['VOTES']==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "bc8db182",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    435\n",
       "True      69\n",
       "Name: VOTES, dtype: int64"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(fandango['VOTES']==0).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "24f3fca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "69"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(fandango['VOTES']==0).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "179a2c67",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Create DataFrame of only reviewed films by removing any films that have zero votes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "d127515a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Valiyavan (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>WWE SummerSlam 2015 (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>Yagavarayinum Naa Kaakka (2015)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>Yesterday, Today and Tomorrow (1964)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Zarafa (2012)</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>504 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     FILM  STARS  RATING  VOTES  YEAR\n",
       "0             Fifty Shades of Grey (2015)    4.0     3.9  34846  2015\n",
       "1                   Jurassic World (2015)    4.5     4.5  34390  2015\n",
       "2                  American Sniper (2015)    5.0     4.8  34085  2015\n",
       "3                        Furious 7 (2015)    5.0     4.8  33538  2015\n",
       "4                       Inside Out (2015)    4.5     4.5  15749  2015\n",
       "..                                    ...    ...     ...    ...   ...\n",
       "499                      Valiyavan (2015)    0.0     0.0      0  2015\n",
       "500            WWE SummerSlam 2015 (2015)    0.0     0.0      0  2015\n",
       "501       Yagavarayinum Naa Kaakka (2015)    0.0     0.0      0  2015\n",
       "502  Yesterday, Today and Tomorrow (1964)    0.0     0.0      0  1964\n",
       "503                         Zarafa (2012)    0.0     0.0      0  2012\n",
       "\n",
       "[504 rows x 5 columns]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fandango"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "527fe93c",
   "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>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>That Sugar Film (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>The Intern (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>The Park Bench (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>The Wanted 18 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>Z For Zachariah (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            FILM  STARS  RATING  VOTES  YEAR\n",
       "0    Fifty Shades of Grey (2015)    4.0     3.9  34846  2015\n",
       "1          Jurassic World (2015)    4.5     4.5  34390  2015\n",
       "2         American Sniper (2015)    5.0     4.8  34085  2015\n",
       "3               Furious 7 (2015)    5.0     4.8  33538  2015\n",
       "4              Inside Out (2015)    4.5     4.5  15749  2015\n",
       "..                           ...    ...     ...    ...   ...\n",
       "430       That Sugar Film (2015)    5.0     5.0      1  2015\n",
       "431            The Intern (2015)    5.0     5.0      1  2015\n",
       "432        The Park Bench (2015)    5.0     5.0      1  2015\n",
       "433         The Wanted 18 (2015)    5.0     5.0      1  2015\n",
       "434       Z For Zachariah (2015)    5.0     5.0      1  2015\n",
       "\n",
       "[435 rows x 5 columns]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviewed_films = fandango[fandango['VOTES']!=0]\n",
    "\n",
    "reviewed_films"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3cc62fb",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Create a KDE plot (or multiple kdeplots) that displays the distribution of ratings that are displayed (STARS) versus what the true rating was from votes (RATING). Clip the KDEs to 0-5.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "a796c97e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 5000x2000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.ticker import MaxNLocator  # Ensure MaxNLocator is imported\n",
    "\n",
    "plt.figure(figsize=[10,4], dpi=500)\n",
    "\n",
    "sns.kdeplot(reviewed_films['RATING'], clip=[0, 5], shade=True, label='True Rating')\n",
    "sns.kdeplot(reviewed_films['STARS'], clip=[0, 5], shade=True, label='Stars Displayed')\n",
    "\n",
    "plt.title('KDE Plot for True Rating & the Stars Displayed Comparism')\n",
    "# plt.xlim(0, 5) The clip already catered to the ranges\n",
    "# plt.ylim(0.0, 0.6) The clip already catered to the ranges\n",
    "\n",
    "# plt.gca().xaxis.set_major_locator(MaxNLocator(integer=True))  # Display integers on x-axis\n",
    "# plt.gca().yaxis.set_major_locator(MaxNLocator(integer=True))  # Display integers on y-axis\n",
    "\n",
    "plt.legend(loc=(1.05, 0.5)) \n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbc1d8da",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> TASK: Let's now actually quantify this discrepancy. Create a new column of the different between STARS displayed versus true RATING. Calculate this difference with STARS-RATING and round these differences to the nearest decimal point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "cad6d5f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "reviewed_films['STARS_DIFF'] = round(reviewed_films['STARS'] - reviewed_films['RATING'], 2)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "b2c089a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STARS_DIFF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>That Sugar Film (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>The Intern (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>432</th>\n",
       "      <td>The Park Bench (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>433</th>\n",
       "      <td>The Wanted 18 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>434</th>\n",
       "      <td>Z For Zachariah (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>435 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF\n",
       "0    Fifty Shades of Grey (2015)    4.0     3.9  34846  2015         0.1\n",
       "1          Jurassic World (2015)    4.5     4.5  34390  2015         0.0\n",
       "2         American Sniper (2015)    5.0     4.8  34085  2015         0.2\n",
       "3               Furious 7 (2015)    5.0     4.8  33538  2015         0.2\n",
       "4              Inside Out (2015)    4.5     4.5  15749  2015         0.0\n",
       "..                           ...    ...     ...    ...   ...         ...\n",
       "430       That Sugar Film (2015)    5.0     5.0      1  2015         0.0\n",
       "431            The Intern (2015)    5.0     5.0      1  2015         0.0\n",
       "432        The Park Bench (2015)    5.0     5.0      1  2015         0.0\n",
       "433         The Wanted 18 (2015)    5.0     5.0      1  2015         0.0\n",
       "434       Z For Zachariah (2015)    5.0     5.0      1  2015         0.0\n",
       "\n",
       "[435 rows x 6 columns]"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviewed_films"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b39a1f2e",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> TASK: Create a count plot to display the number of times a certain difference occurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "6984473f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "sns.countplot(data = reviewed_films, x='STARS_DIFF');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a925cb96",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> TASK: We can see from the plot that one movie was displaying over a 1 star difference than its true rating! What movie had this close to 1 star differential?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "9c39251b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>STARS_DIFF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>Turbo Kid (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2015</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 FILM  STARS  RATING  VOTES  YEAR  STARS_DIFF\n",
       "381  Turbo Kid (2015)    5.0     4.0      2  2015         1.0"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reviewed_films[reviewed_films['STARS_DIFF']>=1.0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ff2ffd4",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> New Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "94c800e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sites = pd.read_csv(r\"C:\\Users\\Teni\\Desktop\\Git-Github\\06-Capstone-Project\\all_sites_scores.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "2e051c37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Mr. Holmes (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>78</td>\n",
       "      <td>67</td>\n",
       "      <td>7.9</td>\n",
       "      <td>7.4</td>\n",
       "      <td>33</td>\n",
       "      <td>7367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>'71 (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.2</td>\n",
       "      <td>60</td>\n",
       "      <td>24116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Two Days, One Night (2014)</td>\n",
       "      <td>97</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "      <td>8.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>123</td>\n",
       "      <td>24345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Gett: The Trial of Viviane Amsalem (2015)</td>\n",
       "      <td>100</td>\n",
       "      <td>81</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>7.8</td>\n",
       "      <td>19</td>\n",
       "      <td>1955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>63</td>\n",
       "      <td>68</td>\n",
       "      <td>6.4</td>\n",
       "      <td>6.7</td>\n",
       "      <td>19</td>\n",
       "      <td>5289</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>146 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          FILM  RottenTomatoes  \\\n",
       "0               Avengers: Age of Ultron (2015)              74   \n",
       "1                            Cinderella (2015)              85   \n",
       "2                               Ant-Man (2015)              80   \n",
       "3                       Do You Believe? (2015)              18   \n",
       "4                Hot Tub Time Machine 2 (2015)              14   \n",
       "..                                         ...             ...   \n",
       "141                          Mr. Holmes (2015)              87   \n",
       "142                                 '71 (2015)              97   \n",
       "143                 Two Days, One Night (2014)              97   \n",
       "144  Gett: The Trial of Viviane Amsalem (2015)             100   \n",
       "145         Kumiko, The Treasure Hunter (2015)              87   \n",
       "\n",
       "     RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0                     86          66              7.1   7.8   \n",
       "1                     80          67              7.5   7.1   \n",
       "2                     90          64              8.1   7.8   \n",
       "3                     84          22              4.7   5.4   \n",
       "4                     28          29              3.4   5.1   \n",
       "..                   ...         ...              ...   ...   \n",
       "141                   78          67              7.9   7.4   \n",
       "142                   82          83              7.5   7.2   \n",
       "143                   78          89              8.8   7.4   \n",
       "144                   81          90              7.3   7.8   \n",
       "145                   63          68              6.4   6.7   \n",
       "\n",
       "     Metacritic_user_vote_count  IMDB_user_vote_count  \n",
       "0                          1330                271107  \n",
       "1                           249                 65709  \n",
       "2                           627                103660  \n",
       "3                            31                  3136  \n",
       "4                            88                 19560  \n",
       "..                          ...                   ...  \n",
       "141                          33                  7367  \n",
       "142                          60                 24116  \n",
       "143                         123                 24345  \n",
       "144                          19                  1955  \n",
       "145                          19                  5289  \n",
       "\n",
       "[146 rows x 8 columns]"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "04c6a13c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "0  Avengers: Age of Ultron (2015)              74                   86   \n",
       "1               Cinderella (2015)              85                   80   \n",
       "2                  Ant-Man (2015)              80                   90   \n",
       "3          Do You Believe? (2015)              18                   84   \n",
       "4   Hot Tub Time Machine 2 (2015)              14                   28   \n",
       "\n",
       "   Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "0          66              7.1   7.8                        1330   \n",
       "1          67              7.5   7.1                         249   \n",
       "2          64              8.1   7.8                         627   \n",
       "3          22              4.7   5.4                          31   \n",
       "4          29              3.4   5.1                          88   \n",
       "\n",
       "   IMDB_user_vote_count  \n",
       "0                271107  \n",
       "1                 65709  \n",
       "2                103660  \n",
       "3                  3136  \n",
       "4                 19560  "
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "d2e53989",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 8 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      "dtypes: float64(2), int64(5), object(1)\n",
      "memory usage: 9.2+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "056053f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "      <td>146.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>60.849315</td>\n",
       "      <td>63.876712</td>\n",
       "      <td>58.808219</td>\n",
       "      <td>6.519178</td>\n",
       "      <td>6.736986</td>\n",
       "      <td>185.705479</td>\n",
       "      <td>42846.205479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>30.168799</td>\n",
       "      <td>20.024430</td>\n",
       "      <td>19.517389</td>\n",
       "      <td>1.510712</td>\n",
       "      <td>0.958736</td>\n",
       "      <td>316.606515</td>\n",
       "      <td>67406.509171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>243.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>31.250000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>43.500000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>6.300000</td>\n",
       "      <td>33.250000</td>\n",
       "      <td>5627.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>63.500000</td>\n",
       "      <td>66.500000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>6.850000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>72.500000</td>\n",
       "      <td>19103.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>75.000000</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>7.400000</td>\n",
       "      <td>168.500000</td>\n",
       "      <td>45185.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>94.000000</td>\n",
       "      <td>9.600000</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>2375.000000</td>\n",
       "      <td>334164.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       RottenTomatoes  RottenTomatoes_User  Metacritic  Metacritic_User  \\\n",
       "count      146.000000           146.000000  146.000000       146.000000   \n",
       "mean        60.849315            63.876712   58.808219         6.519178   \n",
       "std         30.168799            20.024430   19.517389         1.510712   \n",
       "min          5.000000            20.000000   13.000000         2.400000   \n",
       "25%         31.250000            50.000000   43.500000         5.700000   \n",
       "50%         63.500000            66.500000   59.000000         6.850000   \n",
       "75%         89.000000            81.000000   75.000000         7.500000   \n",
       "max        100.000000            94.000000   94.000000         9.600000   \n",
       "\n",
       "             IMDB  Metacritic_user_vote_count  IMDB_user_vote_count  \n",
       "count  146.000000                  146.000000            146.000000  \n",
       "mean     6.736986                  185.705479          42846.205479  \n",
       "std      0.958736                  316.606515          67406.509171  \n",
       "min      4.000000                    4.000000            243.000000  \n",
       "25%      6.300000                   33.250000           5627.000000  \n",
       "50%      6.900000                   72.500000          19103.000000  \n",
       "75%      7.400000                  168.500000          45185.750000  \n",
       "max      8.600000                 2375.000000         334164.000000  "
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14359469",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "Let's first take a look at Rotten Tomatoes. RT has two sets of reviews, their critics reviews (ratings published by official critics) and user reviews. \n",
    "\n",
    "**TASK: Create a scatterplot exploring the relationship between RT Critic reviews and RT User reviews.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "b8774ff3",
   "metadata": {},
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "sns.scatterplot(data=all_sites, x='RottenTomatoes', y= 'RottenTomatoes_User', s=80)\n",
    "\n",
    "plt.xlim(0,100)\n",
    "plt.ylim(0, 100);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dc24ac06",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "Let's quantify this difference by comparing the critics ratings and the RT User ratings. We will calculate this with RottenTomatoes-RottenTomatoes_User. Note: diff here is Critics - User Score. So values closer to 0 means aggrement between Critics and Users. Larger positive values means critics rated much higher than users. Larger negative values means users rated much higher than critics.\n",
    "\n",
    "**TASK: Create a new column based off the difference between critics ratings and users ratings for Rotten Tomatoes. Calculate this with RottenTomatoes-RottenTomatoes_User**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "c814be17",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_sites['diff'] = round(all_sites['RottenTomatoes'] - all_sites['RottenTomatoes_User'], 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "5a0780d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "      <td>-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "      <td>-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "      <td>-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Mr. Holmes (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>78</td>\n",
       "      <td>67</td>\n",
       "      <td>7.9</td>\n",
       "      <td>7.4</td>\n",
       "      <td>33</td>\n",
       "      <td>7367</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>'71 (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.2</td>\n",
       "      <td>60</td>\n",
       "      <td>24116</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Two Days, One Night (2014)</td>\n",
       "      <td>97</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "      <td>8.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>123</td>\n",
       "      <td>24345</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Gett: The Trial of Viviane Amsalem (2015)</td>\n",
       "      <td>100</td>\n",
       "      <td>81</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>7.8</td>\n",
       "      <td>19</td>\n",
       "      <td>1955</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>63</td>\n",
       "      <td>68</td>\n",
       "      <td>6.4</td>\n",
       "      <td>6.7</td>\n",
       "      <td>19</td>\n",
       "      <td>5289</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>146 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          FILM  RottenTomatoes  \\\n",
       "0               Avengers: Age of Ultron (2015)              74   \n",
       "1                            Cinderella (2015)              85   \n",
       "2                               Ant-Man (2015)              80   \n",
       "3                       Do You Believe? (2015)              18   \n",
       "4                Hot Tub Time Machine 2 (2015)              14   \n",
       "..                                         ...             ...   \n",
       "141                          Mr. Holmes (2015)              87   \n",
       "142                                 '71 (2015)              97   \n",
       "143                 Two Days, One Night (2014)              97   \n",
       "144  Gett: The Trial of Viviane Amsalem (2015)             100   \n",
       "145         Kumiko, The Treasure Hunter (2015)              87   \n",
       "\n",
       "     RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0                     86          66              7.1   7.8   \n",
       "1                     80          67              7.5   7.1   \n",
       "2                     90          64              8.1   7.8   \n",
       "3                     84          22              4.7   5.4   \n",
       "4                     28          29              3.4   5.1   \n",
       "..                   ...         ...              ...   ...   \n",
       "141                   78          67              7.9   7.4   \n",
       "142                   82          83              7.5   7.2   \n",
       "143                   78          89              8.8   7.4   \n",
       "144                   81          90              7.3   7.8   \n",
       "145                   63          68              6.4   6.7   \n",
       "\n",
       "     Metacritic_user_vote_count  IMDB_user_vote_count  diff  \n",
       "0                          1330                271107   -12  \n",
       "1                           249                 65709     5  \n",
       "2                           627                103660   -10  \n",
       "3                            31                  3136   -66  \n",
       "4                            88                 19560   -14  \n",
       "..                          ...                   ...   ...  \n",
       "141                          33                  7367     9  \n",
       "142                          60                 24116    15  \n",
       "143                         123                 24345    19  \n",
       "144                          19                  1955    19  \n",
       "145                          19                  5289    24  \n",
       "\n",
       "[146 rows x 9 columns]"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46c26641",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "Let's now compare the overall mean difference. Since we're dealing with differences that could be negative or positive, first take the absolute value of all the differences, then take the mean. This would report back on average to absolute difference between the critics rating versus the user rating.\n",
    "\n",
    "**TASK: Calculate the Mean Absolute Difference between RT scores and RT User scores as described above.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "86bca17d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.095890410958905"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites['diff'].apply(abs).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db22886f",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "\n",
    "**TASK: Plot the distribution of the differences between RT Critics Score and RT User Score. There should be negative values in this distribution plot. Feel free to use KDE or Histograms to display this distribution.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "c56802e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2400x1200 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 6], dpi=200)\n",
    "sns.displot(data=all_sites,x='diff', kde=True, bins=25)\n",
    "\n",
    "plot.set_axis_labels(\"Rotten_Diff\")\n",
    "plot.fig.suptitle('RT Critics Score minus RT User Score', y=1.02)  # Title for the plot\n",
    "\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# sns.displot(data=sample_ages, x='age', rug=True, bins=30, kde=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8fd84a6",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "\n",
    "**TASK: Now create a distribution showing the *absolute value* difference between Critics and Users on Rotten Tomatoes.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "ff7d66ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "      <th>task_need</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Avengers: Age of Ultron (2015)</td>\n",
       "      <td>74</td>\n",
       "      <td>86</td>\n",
       "      <td>66</td>\n",
       "      <td>7.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>1330</td>\n",
       "      <td>271107</td>\n",
       "      <td>-12</td>\n",
       "      <td>27.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cinderella (2015)</td>\n",
       "      <td>85</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.1</td>\n",
       "      <td>249</td>\n",
       "      <td>65709</td>\n",
       "      <td>5</td>\n",
       "      <td>10.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ant-Man (2015)</td>\n",
       "      <td>80</td>\n",
       "      <td>90</td>\n",
       "      <td>64</td>\n",
       "      <td>8.1</td>\n",
       "      <td>7.8</td>\n",
       "      <td>627</td>\n",
       "      <td>103660</td>\n",
       "      <td>-10</td>\n",
       "      <td>25.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>18</td>\n",
       "      <td>84</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>31</td>\n",
       "      <td>3136</td>\n",
       "      <td>-66</td>\n",
       "      <td>81.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hot Tub Time Machine 2 (2015)</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>29</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>88</td>\n",
       "      <td>19560</td>\n",
       "      <td>-14</td>\n",
       "      <td>29.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Mr. Holmes (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>78</td>\n",
       "      <td>67</td>\n",
       "      <td>7.9</td>\n",
       "      <td>7.4</td>\n",
       "      <td>33</td>\n",
       "      <td>7367</td>\n",
       "      <td>9</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>'71 (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>82</td>\n",
       "      <td>83</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7.2</td>\n",
       "      <td>60</td>\n",
       "      <td>24116</td>\n",
       "      <td>15</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Two Days, One Night (2014)</td>\n",
       "      <td>97</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "      <td>8.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>123</td>\n",
       "      <td>24345</td>\n",
       "      <td>19</td>\n",
       "      <td>-3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Gett: The Trial of Viviane Amsalem (2015)</td>\n",
       "      <td>100</td>\n",
       "      <td>81</td>\n",
       "      <td>90</td>\n",
       "      <td>7.3</td>\n",
       "      <td>7.8</td>\n",
       "      <td>19</td>\n",
       "      <td>1955</td>\n",
       "      <td>19</td>\n",
       "      <td>-3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "      <td>87</td>\n",
       "      <td>63</td>\n",
       "      <td>68</td>\n",
       "      <td>6.4</td>\n",
       "      <td>6.7</td>\n",
       "      <td>19</td>\n",
       "      <td>5289</td>\n",
       "      <td>24</td>\n",
       "      <td>-8.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>146 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          FILM  RottenTomatoes  \\\n",
       "0               Avengers: Age of Ultron (2015)              74   \n",
       "1                            Cinderella (2015)              85   \n",
       "2                               Ant-Man (2015)              80   \n",
       "3                       Do You Believe? (2015)              18   \n",
       "4                Hot Tub Time Machine 2 (2015)              14   \n",
       "..                                         ...             ...   \n",
       "141                          Mr. Holmes (2015)              87   \n",
       "142                                 '71 (2015)              97   \n",
       "143                 Two Days, One Night (2014)              97   \n",
       "144  Gett: The Trial of Viviane Amsalem (2015)             100   \n",
       "145         Kumiko, The Treasure Hunter (2015)              87   \n",
       "\n",
       "     RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0                     86          66              7.1   7.8   \n",
       "1                     80          67              7.5   7.1   \n",
       "2                     90          64              8.1   7.8   \n",
       "3                     84          22              4.7   5.4   \n",
       "4                     28          29              3.4   5.1   \n",
       "..                   ...         ...              ...   ...   \n",
       "141                   78          67              7.9   7.4   \n",
       "142                   82          83              7.5   7.2   \n",
       "143                   78          89              8.8   7.4   \n",
       "144                   81          90              7.3   7.8   \n",
       "145                   63          68              6.4   6.7   \n",
       "\n",
       "     Metacritic_user_vote_count  IMDB_user_vote_count  diff  task_need  \n",
       "0                          1330                271107   -12       27.1  \n",
       "1                           249                 65709     5       10.1  \n",
       "2                           627                103660   -10       25.1  \n",
       "3                            31                  3136   -66       81.1  \n",
       "4                            88                 19560   -14       29.1  \n",
       "..                          ...                   ...   ...        ...  \n",
       "141                          33                  7367     9        6.1  \n",
       "142                          60                 24116    15        0.1  \n",
       "143                         123                 24345    19       -3.9  \n",
       "144                          19                  1955    19       -3.9  \n",
       "145                          19                  5289    24       -8.9  \n",
       "\n",
       "[146 rows x 10 columns]"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abs_mean = all_sites['diff'].apply(abs).mean()\n",
    "\n",
    "all_sites['task_need'] = round(abs_mean-all_sites['diff'], 2)\n",
    "\n",
    "all_sites"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "f3150bcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 2400x1600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "sns.displot(x=all_sites['diff'].apply(abs), bins=25, kde=True)\n",
    "\n",
    "plt.title('Abs Difference between RT Critics Score and RT User Score')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "d835b2bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "sns.histplot(x=all_sites['diff'].apply(abs), bins=25, kde=True)\n",
    "\n",
    "plt.title('Abs Difference between RT Critics Score and RT User Score')\n",
    "plt.show()\n",
    "\n",
    "# Apparently the Histplot is neater and more srisp than the displot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f19a5d1",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "\n",
    "**TASK: What are the top 5 movies users rated higher than critics on average:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "5a78a10e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 10 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      " 8   diff                        146 non-null    int64  \n",
      " 9   task_need                   146 non-null    float64\n",
      "dtypes: float64(3), int64(6), object(1)\n",
      "memory usage: 11.5+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "33b46e2a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Users Love but Critics Hate\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Little Boy (2015)</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>The Longest Ride (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>The Wedding Ringer (2015)</td>\n",
       "      <td>-39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  diff\n",
       "3       Do You Believe? (2015)   -66\n",
       "85           Little Boy (2015)   -61\n",
       "105    Hitman: Agent 47 (2015)   -42\n",
       "134    The Longest Ride (2015)   -42\n",
       "125  The Wedding Ringer (2015)   -39"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Users Love but Critics Hate')\n",
    "all_sites.nsmallest(5, 'diff')[['FILM', 'diff']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26c796b6",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "45f71af0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Users Love but Critics Hate\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Little Boy (2015)</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>The Longest Ride (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>The Wedding Ringer (2015)</td>\n",
       "      <td>-39</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  diff\n",
       "3       Do You Believe? (2015)   -66\n",
       "85           Little Boy (2015)   -61\n",
       "134    The Longest Ride (2015)   -42\n",
       "105    Hitman: Agent 47 (2015)   -42\n",
       "125  The Wedding Ringer (2015)   -39"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Users Love but Critics Hate')\n",
    "all_sites.sort_values('diff', ascending=True)[['FILM', 'diff']].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edac24b3",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "e5f898a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Users Love but Critics Hate\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>The Wedding Ringer (2015)</td>\n",
       "      <td>-39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>The Longest Ride (2015)</td>\n",
       "      <td>-42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Little Boy (2015)</td>\n",
       "      <td>-61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Do You Believe? (2015)</td>\n",
       "      <td>-66</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  diff\n",
       "125  The Wedding Ringer (2015)   -39\n",
       "105    Hitman: Agent 47 (2015)   -42\n",
       "134    The Longest Ride (2015)   -42\n",
       "85           Little Boy (2015)   -61\n",
       "3       Do You Believe? (2015)   -66"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Users Love but Critics Hate')\n",
    "all_sites.sort_values('diff', ascending=False)[['FILM', 'diff']].tail(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81d5b5c4",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> Rotten Tomatoes\n",
    "\n",
    "\n",
    "**TASK: Now show the top 5 movies critics scores higher than users on average.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "35df063f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Critics love, but Users Hate\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Mr. Turner (2014)</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>It Follows (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>While We're Young (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Welcome to Me (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>I'll See You In My Dreams (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 FILM  diff\n",
       "69                  Mr. Turner (2014)    42\n",
       "112                 It Follows (2015)    31\n",
       "115          While We're Young (2015)    31\n",
       "37               Welcome to Me (2015)    24\n",
       "40   I'll See You In My Dreams (2015)    24"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Critics love, but Users Hate')\n",
    "all_sites.nlargest(5, 'diff')[['FILM', 'diff']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4784bf0f",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "c74fc13d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Critics love, but Users Hate\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Mr. Turner (2014)</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>It Follows (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>While We're Young (2015)</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Welcome to Me (2015)</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   FILM  diff\n",
       "69                    Mr. Turner (2014)    42\n",
       "112                   It Follows (2015)    31\n",
       "115            While We're Young (2015)    31\n",
       "145  Kumiko, The Treasure Hunter (2015)    24\n",
       "37                 Welcome to Me (2015)    24"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Critics love, but Users Hate')\n",
    "all_sites.sort_values('diff', ascending=False)[['FILM', 'diff']].head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c70582dc",
   "metadata": {},
   "source": [
    "## MetaCritic\n",
    "\n",
    "Now let's take a quick look at the ratings from MetaCritic. Metacritic also shows an average user rating versus their official displayed rating.\n",
    "\n",
    "**TASK: Display a scatterplot of the Metacritic Rating versus the Metacritic User rating.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "01b1eae7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 10 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      " 8   diff                        146 non-null    int64  \n",
      " 9   task_need                   146 non-null    float64\n",
      "dtypes: float64(3), int64(6), object(1)\n",
      "memory usage: 11.5+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "b9c5f1b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "sns.scatterplot(data= all_sites, x= 'Metacritic',y= 'Metacritic_User', s=80)\n",
    "\n",
    "plt.xlim(0, 100)\n",
    "plt.ylim(0, 10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e93b49b",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> IMDB\n",
    "\n",
    "\n",
    "Finally let's explore IMDB. Notice that both Metacritic and IMDB report back vote counts. Let's analyze the most popular movies.\n",
    "\n",
    "**TASK: Create a scatterplot for the relationship between vote counts on MetaCritic versus vote counts on IMDB.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "2c50caec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 10 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      " 8   diff                        146 non-null    int64  \n",
      " 9   task_need                   146 non-null    float64\n",
      "dtypes: float64(3), int64(6), object(1)\n",
      "memory usage: 11.5+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "id": "61ba922f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "\n",
    "sns.scatterplot(data=all_sites, x= 'Metacritic_user_vote_count', y='IMDB_user_vote_count',s=70)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acd18819",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> IMDB\n",
    "\n",
    "\n",
    "**Notice there are two outliers here. The movie with the highest vote count on IMDB only has about 500 Metacritic ratings. What is this movie?**\n",
    "\n",
    "**TASK: What movie has the highest IMDB user vote count?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "id": "8be89a8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "      <th>task_need</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>The Imitation Game (2014)</td>\n",
       "      <td>90</td>\n",
       "      <td>92</td>\n",
       "      <td>73</td>\n",
       "      <td>8.2</td>\n",
       "      <td>8.1</td>\n",
       "      <td>566</td>\n",
       "      <td>334164</td>\n",
       "      <td>-2</td>\n",
       "      <td>17.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "14  The Imitation Game (2014)              90                   92   \n",
       "\n",
       "    Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "14          73              8.2   8.1                         566   \n",
       "\n",
       "    IMDB_user_vote_count  diff  task_need  \n",
       "14                334164    -2       17.1  "
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "largest = all_sites[all_sites['Metacritic'] <=500]\n",
    "\n",
    "largest.nlargest(1, 'IMDB_user_vote_count')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25fe9b89",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c837a39a",
   "metadata": {},
   "outputs": [],
   "source": [
    "largest = all_sites[all_sites['Metacritic'] <=500]\n",
    "\n",
    "largest.sort_values('IMDB_user_vote_count', ascending=False).head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4df5c9af",
   "metadata": {},
   "source": [
    "#### <font color = 'blue'> IMDB\n",
    "\n",
    "\n",
    "**TASK: What movie has the highest Metacritic User Vote count?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "id": "73838990",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "      <th>task_need</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Mad Max: Fury Road (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>88</td>\n",
       "      <td>89</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2375</td>\n",
       "      <td>292023</td>\n",
       "      <td>9</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "88  Mad Max: Fury Road (2015)              97                   88   \n",
       "\n",
       "    Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "88          89              8.7   8.3                        2375   \n",
       "\n",
       "    IMDB_user_vote_count  diff  task_need  \n",
       "88                292023     9        6.1  "
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.nlargest(1, 'Metacritic_user_vote_count')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7875800a",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "f066c175",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "      <th>task_need</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>Mad Max: Fury Road (2015)</td>\n",
       "      <td>97</td>\n",
       "      <td>88</td>\n",
       "      <td>89</td>\n",
       "      <td>8.7</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2375</td>\n",
       "      <td>292023</td>\n",
       "      <td>9</td>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         FILM  RottenTomatoes  RottenTomatoes_User  \\\n",
       "88  Mad Max: Fury Road (2015)              97                   88   \n",
       "\n",
       "    Metacritic  Metacritic_User  IMDB  Metacritic_user_vote_count  \\\n",
       "88          89              8.7   8.3                        2375   \n",
       "\n",
       "    IMDB_user_vote_count  diff  task_need  \n",
       "88                292023     9        6.1  "
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sites.sort_values( 'Metacritic_user_vote_count', ascending=False).head(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3a5e639",
   "metadata": {},
   "source": [
    "### <font color = 'blue'> Fandago Scores vs. All Sites\n",
    "\n",
    "Finally let's begin to explore whether or not Fandango artificially displays higher ratings than warranted to boost ticket sales.\n",
    "\n",
    "\n",
    "**TASK: Combine the Fandango Table with the All Sites table. Not every movie in the Fandango table is in the All Sites table, since some Fandango movies have very little or no reviews. We only want to compare movies that are in both DataFrames, so do an *inner* merge to merge together both DataFrames based on the FILM columns.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "a299b755",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 504 entries, 0 to 503\n",
      "Data columns (total 5 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   FILM    504 non-null    object \n",
      " 1   STARS   504 non-null    float64\n",
      " 2   RATING  504 non-null    float64\n",
      " 3   VOTES   504 non-null    int64  \n",
      " 4   YEAR    504 non-null    object \n",
      "dtypes: float64(2), int64(1), object(2)\n",
      "memory usage: 19.8+ KB\n"
     ]
    }
   ],
   "source": [
    "fandango.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "20795524",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 146 entries, 0 to 145\n",
      "Data columns (total 10 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        146 non-null    object \n",
      " 1   RottenTomatoes              146 non-null    int64  \n",
      " 2   RottenTomatoes_User         146 non-null    int64  \n",
      " 3   Metacritic                  146 non-null    int64  \n",
      " 4   Metacritic_User             146 non-null    float64\n",
      " 5   IMDB                        146 non-null    float64\n",
      " 6   Metacritic_user_vote_count  146 non-null    int64  \n",
      " 7   IMDB_user_vote_count        146 non-null    int64  \n",
      " 8   diff                        146 non-null    int64  \n",
      " 9   task_need                   146 non-null    float64\n",
      "dtypes: float64(3), int64(6), object(1)\n",
      "memory usage: 11.5+ KB\n"
     ]
    }
   ],
   "source": [
    "all_sites.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "62e7c74c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.merge(fandango, all_sites,how='inner', on='FILM')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "c36423df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 145 entries, 0 to 144\n",
      "Data columns (total 14 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   FILM                        145 non-null    object \n",
      " 1   STARS                       145 non-null    float64\n",
      " 2   RATING                      145 non-null    float64\n",
      " 3   VOTES                       145 non-null    int64  \n",
      " 4   YEAR                        145 non-null    object \n",
      " 5   RottenTomatoes              145 non-null    int64  \n",
      " 6   RottenTomatoes_User         145 non-null    int64  \n",
      " 7   Metacritic                  145 non-null    int64  \n",
      " 8   Metacritic_User             145 non-null    float64\n",
      " 9   IMDB                        145 non-null    float64\n",
      " 10  Metacritic_user_vote_count  145 non-null    int64  \n",
      " 11  IMDB_user_vote_count        145 non-null    int64  \n",
      " 12  diff                        145 non-null    int64  \n",
      " 13  task_need                   145 non-null    float64\n",
      "dtypes: float64(5), int64(7), object(2)\n",
      "memory usage: 17.0+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "e14c052d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FILM</th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>VOTES</th>\n",
       "      <th>YEAR</th>\n",
       "      <th>RottenTomatoes</th>\n",
       "      <th>RottenTomatoes_User</th>\n",
       "      <th>Metacritic</th>\n",
       "      <th>Metacritic_User</th>\n",
       "      <th>IMDB</th>\n",
       "      <th>Metacritic_user_vote_count</th>\n",
       "      <th>IMDB_user_vote_count</th>\n",
       "      <th>diff</th>\n",
       "      <th>task_need</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "      <td>25</td>\n",
       "      <td>42</td>\n",
       "      <td>46</td>\n",
       "      <td>3.2</td>\n",
       "      <td>4.2</td>\n",
       "      <td>778</td>\n",
       "      <td>179506</td>\n",
       "      <td>-17</td>\n",
       "      <td>32.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "      <td>71</td>\n",
       "      <td>81</td>\n",
       "      <td>59</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>1281</td>\n",
       "      <td>241807</td>\n",
       "      <td>-10</td>\n",
       "      <td>25.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "      <td>72</td>\n",
       "      <td>85</td>\n",
       "      <td>72</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7.4</td>\n",
       "      <td>850</td>\n",
       "      <td>251856</td>\n",
       "      <td>-13</td>\n",
       "      <td>28.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "      <td>81</td>\n",
       "      <td>84</td>\n",
       "      <td>67</td>\n",
       "      <td>6.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>764</td>\n",
       "      <td>207211</td>\n",
       "      <td>-3</td>\n",
       "      <td>18.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "      <td>98</td>\n",
       "      <td>90</td>\n",
       "      <td>94</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>807</td>\n",
       "      <td>96252</td>\n",
       "      <td>8</td>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  STARS  RATING  VOTES  YEAR  RottenTomatoes  \\\n",
       "0  Fifty Shades of Grey (2015)    4.0     3.9  34846  2015              25   \n",
       "1        Jurassic World (2015)    4.5     4.5  34390  2015              71   \n",
       "2       American Sniper (2015)    5.0     4.8  34085  2015              72   \n",
       "3             Furious 7 (2015)    5.0     4.8  33538  2015              81   \n",
       "4            Inside Out (2015)    4.5     4.5  15749  2015              98   \n",
       "\n",
       "   RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0                   42          46              3.2   4.2   \n",
       "1                   81          59              7.0   7.3   \n",
       "2                   85          72              6.6   7.4   \n",
       "3                   84          67              6.8   7.4   \n",
       "4                   90          94              8.9   8.6   \n",
       "\n",
       "   Metacritic_user_vote_count  IMDB_user_vote_count  diff  task_need  \n",
       "0                         778                179506   -17       32.1  \n",
       "1                        1281                241807   -10       25.1  \n",
       "2                         850                251856   -13       28.1  \n",
       "3                         764                207211    -3       18.1  \n",
       "4                         807                 96252     8        7.1  "
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8daf9e36",
   "metadata": {},
   "source": [
    "### Normalize columns to Fandango STARS and RATINGS 0-5 \n",
    "\n",
    "Notice that RT,Metacritic, and IMDB don't use a score between 0-5 stars like Fandango does. In order to do a fair comparison, we need to *normalize* these values so they all fall between 0-5 stars and the relationship between reviews stays the same.\n",
    "\n",
    "**TASK: Create new normalized columns for all ratings so they match up within the 0-5 star range shown on Fandango. There are many ways to do this.**\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "id": "950d214b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['RT_norm']=np.round(df['RottenTomatoes']/20, 1)\n",
    "df['RTU_norm']=np.round(df['RottenTomatoes_User']/20, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "id": "ac844648",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Meta_norm']=np.round(df['Metacritic']/20, 1)\n",
    "df['MetaU_norm']=np.round(df['Metacritic_User']/2, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "id": "99686a9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['IMDB_norm']=np.round(df['IMDB']/2, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "id": "748a97c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "  <thead>\n",
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       "      <th></th>\n",
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       "      <th>STARS</th>\n",
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       "      <th>Metacritic</th>\n",
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       "      <th>IMDB_user_vote_count</th>\n",
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       "      <th>task_need</th>\n",
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       "      <th>RTU_norm</th>\n",
       "      <th>Meta_norm</th>\n",
       "      <th>MetaU_norm</th>\n",
       "      <th>IMDB_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>34846</td>\n",
       "      <td>2015</td>\n",
       "      <td>25</td>\n",
       "      <td>42</td>\n",
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       "      <td>778</td>\n",
       "      <td>179506</td>\n",
       "      <td>-17</td>\n",
       "      <td>32.1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>34390</td>\n",
       "      <td>2015</td>\n",
       "      <td>71</td>\n",
       "      <td>81</td>\n",
       "      <td>59</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>1281</td>\n",
       "      <td>241807</td>\n",
       "      <td>-10</td>\n",
       "      <td>25.1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>American Sniper (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>34085</td>\n",
       "      <td>2015</td>\n",
       "      <td>72</td>\n",
       "      <td>85</td>\n",
       "      <td>72</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7.4</td>\n",
       "      <td>850</td>\n",
       "      <td>251856</td>\n",
       "      <td>-13</td>\n",
       "      <td>28.1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>33538</td>\n",
       "      <td>2015</td>\n",
       "      <td>81</td>\n",
       "      <td>84</td>\n",
       "      <td>67</td>\n",
       "      <td>6.8</td>\n",
       "      <td>7.4</td>\n",
       "      <td>764</td>\n",
       "      <td>207211</td>\n",
       "      <td>-3</td>\n",
       "      <td>18.1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Inside Out (2015)</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>15749</td>\n",
       "      <td>2015</td>\n",
       "      <td>98</td>\n",
       "      <td>90</td>\n",
       "      <td>94</td>\n",
       "      <td>8.9</td>\n",
       "      <td>8.6</td>\n",
       "      <td>807</td>\n",
       "      <td>96252</td>\n",
       "      <td>8</td>\n",
       "      <td>7.1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          FILM  STARS  RATING  VOTES  YEAR  RottenTomatoes  \\\n",
       "0  Fifty Shades of Grey (2015)    4.0     3.9  34846  2015              25   \n",
       "1        Jurassic World (2015)    4.5     4.5  34390  2015              71   \n",
       "2       American Sniper (2015)    5.0     4.8  34085  2015              72   \n",
       "3             Furious 7 (2015)    5.0     4.8  33538  2015              81   \n",
       "4            Inside Out (2015)    4.5     4.5  15749  2015              98   \n",
       "\n",
       "   RottenTomatoes_User  Metacritic  Metacritic_User  IMDB  \\\n",
       "0                   42          46              3.2   4.2   \n",
       "1                   81          59              7.0   7.3   \n",
       "2                   85          72              6.6   7.4   \n",
       "3                   84          67              6.8   7.4   \n",
       "4                   90          94              8.9   8.6   \n",
       "\n",
       "   Metacritic_user_vote_count  IMDB_user_vote_count  diff  task_need  RT_norm  \\\n",
       "0                         778                179506   -17       32.1      1.2   \n",
       "1                        1281                241807   -10       25.1      3.6   \n",
       "2                         850                251856   -13       28.1      3.6   \n",
       "3                         764                207211    -3       18.1      4.0   \n",
       "4                         807                 96252     8        7.1      4.9   \n",
       "\n",
       "   RTU_norm  Meta_norm  MetaU_norm  IMDB_norm  \n",
       "0       2.1        2.3         1.6        2.1  \n",
       "1       4.0        3.0         3.5        3.6  \n",
       "2       4.2        3.6         3.3        3.7  \n",
       "3       4.2        3.4         3.4        3.7  \n",
       "4       4.5        4.7         4.4        4.3  "
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c3839d7",
   "metadata": {},
   "source": [
    "**TASK: Now create a norm_scores DataFrame that only contains the normalizes ratings. Include both STARS and RATING from the original Fandango table.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "id": "6a505f87",
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_scores = df[['STARS', 'RATING', 'RT_norm', 'RTU_norm', 'Meta_norm', 'MetaU_norm', 'IMDB_norm']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "id": "ce39353d",
   "metadata": {},
   "outputs": [
    {
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       "     STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm\n",
       "0      4.0     3.9      1.2       2.1        2.3         1.6        2.1\n",
       "1      4.5     4.5      3.6       4.0        3.0         3.5        3.6\n",
       "2      5.0     4.8      3.6       4.2        3.6         3.3        3.7\n",
       "3      5.0     4.8      4.0       4.2        3.4         3.4        3.7\n",
       "4      4.5     4.5      4.9       4.5        4.7         4.4        4.3\n",
       "..     ...     ...      ...       ...        ...         ...        ...\n",
       "140    3.5     3.5      4.4       3.2        3.4         3.2        3.4\n",
       "141    4.0     3.6      4.8       4.0        4.4         3.2        3.5\n",
       "142    4.5     4.2      4.6       4.2        3.4         3.5        3.9\n",
       "143    4.0     3.9      4.8       4.3        4.3         3.6        3.7\n",
       "144    3.5     3.1      3.0       2.3        3.4         2.9        3.2\n",
       "\n",
       "[145 rows x 7 columns]"
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     "execution_count": 268,
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    "norm_scores"
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  {
   "cell_type": "code",
   "execution_count": 269,
   "id": "daef9a54",
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "   STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm\n",
       "0    4.0     3.9      1.2       2.1        2.3         1.6        2.1\n",
       "1    4.5     4.5      3.6       4.0        3.0         3.5        3.6\n",
       "2    5.0     4.8      3.6       4.2        3.6         3.3        3.7\n",
       "3    5.0     4.8      4.0       4.2        3.4         3.4        3.7\n",
       "4    4.5     4.5      4.9       4.5        4.7         4.4        4.3"
      ]
     },
     "execution_count": 269,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e409c43",
   "metadata": {},
   "source": [
    "### Comparing Distribution of Scores Across Sites\n",
    "\n",
    "\n",
    "Now the moment of truth! Does Fandango display abnormally high ratings? We already know it pushs displayed RATING higher than STARS, but are the ratings themselves higher than average?\n",
    "\n",
    "\n",
    "**TASK: Create a plot comparing the distributions of normalized ratings across all sites. There are many ways to do this, but explore the Seaborn KDEplot docs for some simple ways to quickly show this. Don't worry if your plot format does not look exactly the same as ours, as long as the differences in distribution are clear.**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "id": "6f33b5cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "def move_legend(ax, new_loc, **kws):\n",
    "    old_legend = ax.legend_\n",
    "    handles = old_legend.legendHandles\n",
    "    labels = [t.get_text() for t in old_legend.get_texts()]\n",
    "    title = old_legend.get_title().get_text()\n",
    "    ax.legend(handles, labels, loc=new_loc, title=title, **kws)\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "id": "0b0f1abb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2250x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(15,6),dpi=150)\n",
    "\n",
    "sns.kdeplot(data=norm_scores,clip=[0,5],shade=True,palette='Set1', ax=ax)\n",
    "\n",
    "move_legend(ax, \"upper left\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e926e3e",
   "metadata": {},
   "source": [
    "**Clearly Fandango has an uneven distribution. We can also see that RT critics have the most uniform distribution. Let's directly compare these two.** \n",
    "\n",
    "**TASK: Create a KDE plot that compare the distribution of RT critic ratings against the STARS displayed by Fandango.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "id": "33828993",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 145 entries, 0 to 144\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   STARS       145 non-null    float64\n",
      " 1   RATING      145 non-null    float64\n",
      " 2   RT_norm     145 non-null    float64\n",
      " 3   RTU_norm    145 non-null    float64\n",
      " 4   Meta_norm   145 non-null    float64\n",
      " 5   MetaU_norm  145 non-null    float64\n",
      " 6   IMDB_norm   145 non-null    float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 9.1 KB\n"
     ]
    }
   ],
   "source": [
    "norm_scores.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "id": "3b5853ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=[12, 8], dpi=200)\n",
    "\n",
    "sns.kdeplot(data=norm_scores[['RT_norm', 'STARS']], clip=[0, 5], shade=True, ax=ax)\n",
    "\n",
    "move_legend(ax, 'upper left')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8163755",
   "metadata": {},
   "source": [
    "#### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "id": "ac5d280b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=[12, 8], dpi=200)\n",
    "\n",
    "sns.kdeplot(norm_scores['RT_norm'], clip=[0, 5], shade=True, label='RT_norm')\n",
    "sns.kdeplot(norm_scores[ 'STARS'], clip=[0, 5], shade=True, label='Stars')\n",
    "\n",
    "plt.legend(loc=(0.01, 0.9)) \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f570389",
   "metadata": {},
   "source": [
    "**OPTIONAL TASK: Create a histplot comparing all normalized scores.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 311,
   "id": "b4c37a93",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 145 entries, 0 to 144\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   STARS       145 non-null    float64\n",
      " 1   RATING      145 non-null    float64\n",
      " 2   RT_norm     145 non-null    float64\n",
      " 3   RTU_norm    145 non-null    float64\n",
      " 4   Meta_norm   145 non-null    float64\n",
      " 5   MetaU_norm  145 non-null    float64\n",
      " 6   IMDB_norm   145 non-null    float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 9.1 KB\n"
     ]
    }
   ],
   "source": [
    "norm_scores.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 328,
   "id": "1ab1e732",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax= plt.subplots(figsize=[12, 8], dpi=200)\n",
    "\n",
    "sns.histplot(data=norm_scores, ax=ax, bins=50)\n",
    "\n",
    "move_legend(ax, \"center left\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "394e9393",
   "metadata": {},
   "source": [
    "\n",
    "### How are the worst movies rated across all platforms?\n",
    "\n",
    "**TASK: Create a clustermap visualization of all normalized scores. Note the differences in ratings, highly rated movies should be clustered together versus poorly rated movies. Note: This clustermap does not need to have the FILM titles as the index, feel free to drop it for the clustermap.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "id": "9925be41",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GRmoAAAAAgNhSVlamK664QsOGDdM777yjLl266Ntvv1XHjh1rr6moqNAVV1yh0aNH66677nIsC8vLgZN8N+RfTEeARVVHkkxHgAXpb/3OdARYVLNhpekIsKhy4QrTEWBB2yt/ZDoCLKr6epfpCLAoeYG1v6tmzZqlc889VwsWLKgd69GjR8Q148ePlyRt377drnh1YqYbAAAAAOAKoVBIoVAoYszj8cjj8USMLVu2TD/96U81evRorV69WmeffbbuueceR2e06xNV0R1mphsN8Pl8CgaDpmM02YOmAwAAAACoUyAQUF5eXsRYbm6u/H5/xNi2bds0d+5c5eTk6JFHHtH//u//6v7775fH49G//du/tWBiZrrhoGAwqPz8fNMxmozl5QAAAEBs8vl8ysnJiRg7eZZbkmpqanTxxRfr8ccflyRddNFF+vLLLzV37lx3Fd3MdMc20zPNJSUlxp4djTMHeU1HgEVHd1SYjgALEjztTUeARYnnDTEdARaVbvmr6QiwoGu77aYjwKKEdvSJcYu6lpLXJT09Xeeff37E2Hnnnae33nrLqWj1iq7o5ritmGZ6pnnKlCnGng0AAADg9HXFFVdo8+bNEWPffPONunfv3uJZouteTtENAAAAAIgxU6ZM0eWXX67HH39cY8aM0f/+7/9q3rx5mjdvXu01+/fv186dO/X9999LUm2RnpaWprS0NNuyRFV0Hzv6nV05EIe8Xq8rZ7t/azoAAAAAgKhccsklWrJkiXw+n37729+qZ8+emj17tu64447aa5YtW6ZJkybVvh47dqykuhuzRSOqohtoSCAQMB2hWQ7fd73pCAAAAACi9K//+q/613/913rfnzhxoiZOnOh4Dopu4CSHCt13zNnpqupIG9MRYIHnmd+YjgCLEvv0MB0BFh0ub7yJEMw7p1+y6Qiw6NiuUtMREMcSTQcAAAAAACBeMdONmGL6mDNJetDo0wEAAADEE4puh5ksIt14TrbpY84k6bsh/2L0+QAAAADiB0W3w0wWkW7sHA4AAAAA8YSiG5a1xKy9G2fnATQsafAg0xFgUfjbb01HAOIKzbnc41hplekIiGMU3bCsJWbtmZ0HAAAAEE8ouhFTvF6v8cKbRmoAAAAA7ELRjZgSCARMR6CRGgAAABAH1qxZoyeffFKFhYXas2ePlixZolGjRkmSqqqq9Nhjj+ntt9/Wtm3blJycrOHDh2vmzJnKyMiovce3336rBx98UGvXrlUoFNJ1112nZ599Vl27drWcg3O6AQAAAABxp6KiQllZWZozZ84p71VWVmr9+vWaNm2a1q9fr8WLF+ubb77RjTfeGPH5ESNGKCEhQR988IH++te/6ujRo7rhhhtUU1NjOQcz3XHM7qXap0uTs7MmZZmOAItqtmw3HQEWVK8rNB0BFlWXHjYdARaVVaWajgBLyk0HgEXB0iTTEeCA7OxsZWdn1/lecnKyVqxYETH27LPP6tJLL9XOnTvVrVs3/fWvf9X27du1YcMGnXnmmZKkBQsWKCUlRR988IGGDx9uKQdFdxyze6m26b3WAAAAAE5voVBIoVAoYszj8cjj8UR974MHDyohIUEdO3asfVZCQkLEvb1erxITE7V27VqKbrhLSxxHZtWM80wnAAAAAFCXQCCgvLy8iLHc3Fz5/f6o7hsMBjV16lSNGzeudlb7sssuU/v27fXwww/r8ccfVzgc1sMPP6yamhrt2bPH8r0puhETWuI4Mqsq5zGjDwAAAMQin8+nnJyciLFoZ7mrqqo0duxY1dTU6Pnnn68d79y5s/74xz/q3//93/Wf//mfSkxM1O23364f//jHSkqyviWBohs4SfXnm01HgEU1FUdNR4AFSZ06mI4AxB1vQrXpCLCg/GvrjZYAWGPXUvLjqqqqNGbMGBUVFemDDz6oneU+bsSIEfr2229VWlqqVq1aqWPHjkpLS1PPnj0tP4OiGwAAAABw2jlecG/ZskUffvihUlPrb1LZqVMnSdIHH3ygkpKSiC7njaHohmV2d0M/0enSGR0AAABAyygvL9fWrVtrXxcVFWnjxo1KSUlRRkaGbr31Vq1fv17Lly9XdXW1iouLJUkpKSlq06aNpB+6lZ933nnq3LmzPvnkEz3wwAOaMmWK+vXrZzkHRTcss7sb+omsFPMt1Wztt44/AQAAAIDTCgoKNGzYsNrXx/eCT5gwQX6/X8uWLZMkDRw4MOJzH374oYYOHSpJ2rx5s3w+n/bv368ePXro0UcfbfJEJEU3XKOlmq0dvu96x58BAAAAwFlDhw5VOByu9/2G3jtu5syZmjlzZlQ5KLoRE6wsXWcJOk4WrqSRkBskntPVdARYVFGw33QEWNSlY4XpCLDA24m/p9wiWGq9EzXQVBTdiAlWlq47tZ8cAAAAAJySaDoAAAAAAADxipluuIaT3dNPRCM1AAAAAHah6IZrONk9/UQ0UgMAAABgF4pu4CRe/xzTEWBR9Y7PTUeABfvu+0/TEWBReVk70xFg0bk5/U1HgAUJXq/pCLCobVmZ6QiIY+zpBgAAAADAIcx0w1E+n0/BYNB0jCZ54tFfmY4AAAAAIE5QdMNRwWBQ+fn5pmM0SVXpNtMRAAAAAERpzZo1evLJJ1VYWKg9e/ZoyZIlGjVqVIvnYHk5AAAAACDuVFRUKCsrS3PmmO3ZxEw3cJLqzZ+YjgDEleQrk01HgFVrD5pOAMSVY//7N9MRYFFCW4/pCHBAdna2srOzTceg6AYAAAAAuEMoFFIoFIoY83g88nhi9xsnFN1oFqsN0kpKShy5r5MCt15s9PkAAAAA6hYIBJSXlxcxlpubK7/fbyaQBRTdaBarDdKmTJniyH2dFPzra0afDwAAAKBuPp9POTk5EWOxPMstUXQDAAAAAFwi1peS14WiG4BrhfcUmY4ACxI7dTQdARZVHSk3HQEWJaSkmo4AC5Iu7Gc6Aqw6csR0AsQxim44yuv1NmmJeVP3gAMAAABAXcrLy7V169ba10VFRdq4caNSUlLUrVu3FstB0Q1HBQKBJl3flALdqaZrNFIDAAAA3K+goEDDhg2rfX18L/iECRP08ssvt1gOim64llNN12ikBgAAALjf0KFDFQ6HTceg6EZsacpydJaiQ5UVphPAgqqvd5mOAItCwdamI8Ci8P59piMA8SUYavwaoJkouhFTmrIcvanHkQEAAABAS0s0HQAAAAAAgHjFTDdcq6md0a2ikRoAAAAAu1B0w7Wa2hndKhqpAQAAALALRTdwkqR+Q0xHgEU1ab1MR4AFSZu+Nh0BFp19g+kEsCohJdV0BFgQ+uNfTEeARa37dTUdAXGMPd0AAAAAADiEohsAAAAAAIewvByu5vP5FAwGbb3nE4/+ytb7AQAAAGhZc+fO1dy5c7V9+3ZJUmZmpn7zm98oOzu7xbNQdMPVgsGg8vPzbb1nVek2W+8HAAAAoGWdc845mjlzpnr37i1JWrhwoW666SZt2LBBmZmZLZqFojsOOTH7e7KSkhJH7tvU7E7lAGCfxD49TEeARVWfbDIdARYlmQ4ASxLa8V8KMOWGGyK7g86YMUNz587Vp59+StGN6Dkx+3syJ87Hlpqe3akcAAAAAGJPKBRSKBSKGPN4PPJ4PPV+prq6Wn/84x9VUVGhIUNa/qQiim64mtfrtb3wZk83AAAAEJsCgYDy8vIixnJzc+X3+0+5dtOmTRoyZIiCwaDOOOMMLVmyROeff34LJf0nim64WiAQsP2e7OkGAAAAYpPP51NOTk7EWH2z3P369dPGjRt14MABvfXWW5owYYJWr17d4oU3RTcAAAAAwBUaW0p+ojZt2tQ2Urv44ov12Wef6ZlnntGLL77oZMRTUHQDcK1w8bemI8CChJRU0xGAuBPev890BFjQuv+5piPAoprSA6YjoAWEw+FT9oO3BIpuOKK5HdTpRg4AAAAgWo888oiys7N17rnn6vDhw1q0aJFWrVqld999t8WzUHTDEc3toH68KVpLHHtWHxqpAQAAAO62d+9ejR8/Xnv27FFycrIuvPBCvfvuu7r22mtbPAtFN2JSSxx7Vh8aqQEAAADuNn/+fNMRatladJucnYxVLJcGAAAAgNOXrUW3ydnJWGX3GdIA4DY0fHKPY6VVpiPAIk/mxaYjwIKaLwtMR4BFiV5r3bCB5kg0HQA4kdfr1ZQpU1ghAAAAACAusKcbMSUQCEhqeIWA09sYaKQGAAAAwC4U3XAdp7cx0EgNAAAAgF0ougEAjgrv3mM6AixKaseuM7cIl+01HQEW1GzZbjoCLEo8p6vpCIhj/O0KAAAAAIBDmOlGTDreUK0uNFkDAAAA4BYU3YhJxxuq1eXEYtyJpmo0UgMAAABgF4puNEtDM9FSy81GO9FUjUZqAAAAQHwJBAJ65JFH9MADD2j27NmSpIkTJ2rhwoUR1w0ePFiffvqprc+m6EazNDQTLTV85Fe0Tiz4WWp+mvO2N50AFiSck246AiyqWMGfqW7haXuG6QhAfAmGTCeAgz777DPNmzdPF1544SnvXXfddVqwYEHt6zZt2tj+fIpuuM6JBb+TxT0AAAAAdysvL9cdd9yhl156SdOnTz/lfY/Ho7S0NEcz0L0cAAAAAOAKoVBIhw4divgKhepfqXDvvfdq5MiRGj58eJ3vr1q1Sl26dFHfvn111113ObKSlpluuFpje8ubg0ZqAAAAQGwKBALKy8uLGMvNzZXf7z/l2kWLFqmwsFAFBQV13is7O1ujR49W9+7dVVRUpGnTpulf/uVfVFhYKI/HY1tmim64WmN7y5uDRmoAAABAbPL5fMrJyYkYq6tA3rVrlx544AG9//778nq9dd7rtttuq/3xgAEDdPHFF6t79+7685//rJtvvtm2zBTdwEmqN39iOgIsCpftNR0BiCsdr+1iOgIQV5IGDzIdAVZVVphOAIs8Ho+lWejCwkKVlJRo0KB//j6srq7WmjVrNGfOHIVCISUlJUV8Jj09Xd27d9eWLVtszUzRDQAAAACIK9dcc402bdoUMTZp0iT1799fDz/88CkFtyTt27dPu3btUnq6vSevUHTDcT6fT8Fg0HQMywK3Xmw6AgAAAIAodOjQQQMGDIgYa9++vVJTUzVgwACVl5fL7/frlltuUXp6urZv365HHnlEnTp10s9+9jNbs1B0w3HBYFD5+fmmY1gW/OtrpiMAAAAAcFBSUpI2bdqkV155RQcOHFB6erqGDRumN998Ux06dLD1WRTdAAAAAIC4t2rVqtoft23bVu+9916LPJeiGzhJUr8hpiPAopqD9p+jCPuFz/rWdARYdGzLf5uOAIsS03qZjgALqt59x3QEWETTOziJohuOOPH8bCcOmAcAAAAAN6DohiNOPD/7ePEdjZZsxvbEo79qkecAAAAAiH8U3XCFlmzGVlW6rUWeAwAAACD+JZoOAAAAAABAvGKmG447cX93c7EvHHUJHyg2HQEAjAgHD5uOAAuSLuhvOgIsCu/fZzoC4hhFNxx34v7u5rJjXzgAAAAAtDSKbriCHbPlVtFIDQAAAIBdKLrhCnbMlltFIzUAAADA3Xr06KEdO3acMn7PPffoueeeUzgcVl5enubNm6eysjINHjxYzz33nDIzM23PQtENnKRq8bOmI8CqsgOmE8CCmtIDpiPAooqC/aYjwCJv6RzTEWBB6/7nmo4Ai6p37TUdATb77LPPVF1dXfv6iy++0LXXXqvRo0dLkp544gk9/fTTevnll9W3b19Nnz5d1157rTZv3qwOHTrYmoXu5QAAAACAuNK5c2elpaXVfi1fvly9evXS1VdfrXA4rNmzZ+vRRx/VzTffrAEDBmjhwoWqrKzU66+/bnsWim4AAAAAgCuEQiEdOnQo4isUCjX4maNHj+rVV1/VnXfeqYSEBBUVFam4uFgjRoyovcbj8ejqq6/Wxx9/bHtmlpfDNXw+n4LBoOPPmXGe448AAAAA0AyBQEB5eXkRY7m5ufL7/fV+ZunSpTpw4IAmTpwoSSou/uHY2a5du0Zc17Vr1zr3gUeLohuuEQwGlZ+f7/hzKudxPBkAAAAQi3w+n3JyciLGPB5Pg5+ZP3++srOzlZGRETGekJAQ8TocDp8yZgeKbrQIO2apS0pKbEqDuHFWR9MJYAH7mNzjSFm56QiwqMN155iOAAtoJOkeCW0bLtoQOzweT6NF9ol27NihlStXavHixbVjaWlpkn6Y8U5PT68dLykpOWX22w4U3WgRdsxSt9Q53QAAAADiw4IFC9SlSxeNHDmydqxnz55KS0vTihUrdNFFF0n6Yd/36tWrNWvWLNszUHQDAAAAAOJOTU2NFixYoAkTJqhVq3+WvgkJCZo8ebIef/xx9enTR3369NHjjz+udu3aady4cbbnoOiGa3i93haZ7aaRGgAAAOB+K1eu1M6dO3XnnXee8t6vf/1rHTlyRPfcc4/Kyso0ePBgvf/++7af0S1RdMNFAoFAizyHRmoAAACA+40YMULhcLjO9xISEuT3+xvsem4Xim4A7nXkiOkEsCChVy/TEWDRWRftMh0BFiVcPMR0BFiQVEYTWLeoXldoOgLiGEU3LIm2+zidxwEAAACcjii6YUm03cebuxfbjqPGmoo93QAAAADsQtGNmGbHUWNNxZ5uAAAAAHZJNB0AAAAAAIB4xUw3AMBR4f37TEeARa37n2s6AiwKf/uV6QgAAIsoutEimnvGNg3YAAAAALgZRTdaRHPP2J4yZUqLN1OjkRoAAAAAu1B0I+a1dDM1GqkBAAAA7tajRw/t2LHjlPF77rlHzz33XMTY3XffrXnz5ik/P1+TJ0+2PQtFNwD3atvWdAJYkNCL5SNucfTV/zIdARa1HugxHQFW8PeUayS05fdUvPnss89UXV1d+/qLL77Qtddeq9GjR0dct3TpUq1bt04ZGRmOZaF7OQAAAAAgrnTu3FlpaWm1X8uXL1evXr109dVX117z3Xff6b777tNrr72m1q1bO5aFmW7ENK/Xq507d5qOAQAAACAGhEIhhUKhiDGPxyOPp/7VCkePHtWrr76qnJwcJSQkSJJqamo0fvx4PfTQQ8rMzHQ0M0U3YlogEKi367lTDdZopAYAAADEpkAgoLy8vIix3Nxc+f3+ej+zdOlSHThwQBMnTqwdmzVrllq1aqX777/foaT/RNEN13KqwRqN1AAAAIDY5PP5lJOTEzHW0Cy3JM2fP1/Z2dm1+7YLCwv1zDPPaP369bUz306i6HZYc8+njka8nW1d369hvP080QxHjphOAAvC335lOgIsOlZaZToCLGodDDV+EcyjkZprhI/we8otGltKfrIdO3Zo5cqVWrx4ce3YRx99pJKSEnXr1q12rLq6Wv/xH/+h2bNna/v27XZGpuh2WnPPp45GSxf5Tqvv1zDefp4AAAAA7LVgwQJ16dJFI0eOrB0bP368hg8fHnHdT3/6U40fP16TJk2yPQNFNwAAAAAg7tTU1GjBggWaMGGCWrX6Z+mbmpqq1NTUiGtbt26ttLQ09evXz/YcFN2nkWgaj8XiUm6nlu7TSA0AAABwv5UrV2rnzp268847jeag6D6NRNN4LBaXcju1dJ9GagAAAID7jRgxQuFw2NK1du/jPhFFN3CS6s83m44Ai6r/QSM1N/CMvMx0BCDuHFm7zXQEWNDu7ptMR4BF1Z9sMh0BcSzRdAAAAAAAAOIVM91olmj2h8e635oOAAAAACBuUHSjWaLZHx7rDt93vekIAAAAAOIEy8sBAAAAAHAIM90AXCuhXZLpCLCiXXvTCWBR2yt/ZDoCLKopPWA6Aiw49u5K0xFgUVKnDqYjII4x0w0AAAAAgEOY6UbcsKu5G43UAAAAANiFohtxw67mbjRSAwAAANzv8OHDmjZtmpYsWaKSkhJddNFFeuaZZ3TJJZdIkvx+vxYtWqRdu3apTZs2GjRokGbMmKHBgwfbmoPl5QAAAACAuPOLX/xCK1as0B/+8Adt2rRJI0aM0PDhw/Xdd99Jkvr27as5c+Zo06ZNWrt2rXr06KERI0boH//4h605mOkGADgqIb2n6QiwKLx/n+kIsKj6612mI8CCxPZtTEcATltHjhzRW2+9pT/96U+66qqrJP0ws7106VLNnTtX06dP17hx4yI+8/TTT2v+/Pn6/PPPdc0119iWhaIbMae5e7NLSkocSAMAAAAgVoRCIYVCoYgxj8cjj8cTMXbs2DFVV1fL6/VGjLdt21Zr16495b5Hjx7VvHnzlJycrKysLFszU3Qj5jR3b/aUKVPqHG9qEU8jNQAAACA2BQIB5eXlRYzl5ubK7/dHjHXo0EFDhgzR7373O5133nnq2rWr3njjDa1bt059+vSpvW758uUaO3asKisrlZ6erhUrVqhTp062ZqboRtxrahFPIzUAAAAgNvl8PuXk5ESMnTzLfdwf/vAH3XnnnTr77LOVlJSkH//4xxo3bpzWr19fe82wYcO0ceNGlZaW6qWXXtKYMWO0bt06denSxbbMFN2wxOv1Rswkx+JS7pMzHheLWYHTSThYYToCrDpyxHQCIK4ktK27EEDsqS49bDoCLDqjjqXk9enVq5dWr16tiooKHTp0SOnp6brtttvUs+c/+820b99evXv3Vu/evXXZZZepT58+mj9/vnw+n22ZKbphSSAQiHhd31Juk07OeFwsZgUAAADQMtq3b6/27durrKxM7733np544ol6rw2Hw6fsGY8WRTcAAAAAIO689957CofD6tevn7Zu3aqHHnpI/fr106RJk1RRUaEZM2boxhtvVHp6uvbt26fnn39eu3fv1ujRo23NQdGNFtGUZmZ2Lwevb9l5fWikBgAAALjfwYMH5fP5tHv3bqWkpOiWW27RjBkz1Lp1a1VXV+vrr7/WwoULVVpaqtTUVF1yySX66KOPlJmZaWsOim60iKY0M7N7OXh9y87rQyM1AAAAwP3GjBmjMWPG1Pme1+vV4sWLWyQHRTdwkqQL+5mOAKs+32w6Aaw4Um46Aaxq29Z0Alh0rLTKdARYQnMut+D3FJyUaDoAAAAAAADxiqIbAAAAAACHsLwcrtCURmzRmnFeizwGAAAAwGmAohuu0JRGbNGqnMe53gAAAADsQdGNmFPXEV92HyOG+JDQ1mM6AixI7JllOgIsqv5yk+kIsKhN9/amI8CCmoqjpiPAoladWpuOgDhG0Y2YU9cRX3YfIwYAAAAALYGiG81S12x0Q6KdqW7q86LBnm4AAAAAdqHoRrPUNRvdkGgL5qY+Lxrs6QYAAADcb82aNXryySdVWFioPXv2aMmSJRo1alTt++FwWHl5eZo3b57Kyso0ePBgPffcc8rMzKy9pri4WA899JBWrFihw4cPq1+/fnrkkUd06623Ws7BkWEAAAAAgLhTUVGhrKwszZkzp873n3jiCT399NOaM2eOPvvsM6Wlpenaa6/V4cOHa68ZP368Nm/erGXLlmnTpk26+eabddttt2nDhg2WczDTDcC1wkdCpiPAgprClaYjwKLD724zHQEWHQsmmY4AC9p3C5uOAIuqK2tMR4ADsrOzlZ2dXed74XBYs2fP1qOPPqqbb75ZkrRw4UJ17dpVr7/+uu6++25J0ieffKK5c+fq0ksvlSQ99thjys/P1/r163XRRRdZysFMNwAAAADAFUKhkA4dOhTxFQo1fSKmqKhIxcXFGjFiRO2Yx+PR1VdfrY8//rh27Morr9Sbb76p/fv3q6amRosWLVIoFNLQoUMtP4uZbsQUn8+nYDBoNAON1AAAAIDYFAgElJeXFzGWm5srv9/fpPsUFxdLkrp27Rox3rVrV+3YsaP29ZtvvqnbbrtNqampatWqldq1a6clS5aoV69elp9F0Y2YEgwGlZ+fbzQDjdQAAACA2OTz+ZSTkxMx5vF4mn2/hISEiNfhcDhi7LHHHlNZWZlWrlypTp06aenSpRo9erQ++ugjXXDBBZaeQdENAAAAAHAFj8cTVZF9XFpamqQfZrzT09Nrx0tKSmpnv7/99lvNmTNHX3zxRW1H86ysLH300Ud67rnn9MILL1h6FkU3WoTVc7ajPc/bDtWfbzYdAYgvZ/c0nQAWeXt8ZjoCLDpWWmU6AiyorjSdAFa16tTadAS0sJ49eyotLU0rVqyobYh29OhRrV69WrNmzZIkVVb+8Js4MTGyFVpSUpJqaqw336PoRouwes52tOd5AwAAAIAklZeXa+vWrbWvi4qKtHHjRqWkpKhbt26aPHmyHn/8cfXp00d9+vTR448/rnbt2mncuHGSpP79+6t37966++679dRTTyk1NVVLly7VihUrtHz5css5KLoRU6zOiDvpt0afDgAAAMAOBQUFGjZsWO3r43vBJ0yYoJdfflm//vWvdeTIEd1zzz0qKyvT4MGD9f7776tDhw6SpNatW+vtt9/W1KlTdcMNN6i8vFy9e/fWwoULdf3111vOQdGNmGJ1RtxJh++z/hsIAAAAQGwaOnSowuFwve8nJCTI7/c32Pm8T58+euutt6LKQdENnMTrn2M6Aiyq3vG56QiwIKn7haYjAHGnzZFy0xFgQfXqj0xHgEWJnTqajoA4ltj4JQAAAAAAoDkougEAAAAAcAjLy9GifD6fgsGg6RgNeuLRX5mOAAAAACBOUHSjRQWDQeXn55uO0aCq0m2mIwAAAACIExTdaLbmzFqXlJQ4lMY+1Zs/MR0BFoX3FJmOACtopOYeZbH/ZzT+P2d1MZ0AFhxce9B0BFh01qiOpiMgjlF0o9maM2tt+gxuAAAAAGhJNFIDAAAAAMAhzHSjRXm93pif7Q7cerHpCAAAAABsFAgE9Mgjj+iBBx7Q7NmzW/TZFN1oUYFAwHSERgX/+prpCAAAAABs8tlnn2nevHm68EIzfWYougG4VkJ6T9MRYEE4WGE6AixKPG+I6QiwKHyg2HQEWJAyfazpCLDqSLnpBHBIeXm57rjjDr300kuaPn26kQzs6QYAAAAAuEIoFNKhQ4civkKhUL3X33vvvRo5cqSGDx/egikjMdMNV2jO8WTNxZ5uAAAAIDYFAgHl5eVFjOXm5srv959y7aJFi1RYWKiCgoIWSlc3im64QnOOJ2v2s9jTDQAAAMQkn8+nnJyciDGPx3PKdbt27dIDDzyg999/X16vt6Xi1YmiGwAAAADgCh6Pp84i+2SFhYUqKSnRoEGDaseqq6u1Zs0azZkzR6FQSElJSU5GrUXRDcC1wmV7TUeABeE0Gqm5Rc1Xn5iOAItoJOkO4S/Wm44AixLOPsd0BNjsmmuu0aZNmyLGJk2apP79++vhhx9usYJbougGAAAAAMSZDh06aMCAARFj7du3V2pq6injTqPoRlyKpvEajdQAAAAA2IWiG0ZZLY5LSkqadN9oGq/RSA0AAACIP6tWrTLyXIpuGGW1OJ4yZUoLpAEAAAAAe1F0xyGv11tnkdrU2eJY19Asebz9XAE3S0zuYjoCLKrxtjMdAVZ525tOAAsSzjrLdARYVUnTTziHojsOBQKBOsfjbba4oVnyePu5AgAAAHAnim7Epfpm+62gkRoAAAAAu1B0Iy7VN9tvBY3UAAAAANiFohuuUNfMNfu2AXeoOcjvVddoe4bpBLAofIDfV65wdk/TCWBVGb+n4ByKbrhCXTPX7NsGAAAAEOsSTQcAAAAAACBeMdONuNLQMWJW0UgNAAAAgF0ouhFXGjpGzPI9aKQGAAAAuN7hw4c1bdo0LVmyRCUlJbrooov0zDPP6JJLLpEkLV68WC+++KIKCwu1b98+bdiwQQMHDrQ9B0U3XIvmaqDpE2AzGgm5RkLPAaYjwAIa3rlHeP8+0xHggF/84hf64osv9Ic//EEZGRl69dVXNXz4cP3973/X2WefrYqKCl1xxRUaPXq07rrrLsdyUHTDtWiuBgAAAKAuR44c0VtvvaU//elPuuqqqyRJfr9fS5cu1dy5czV9+nSNHz9ekrR9+3ZHs1B0AwAAAABcIRQKKRQKRYx5PB55PJ6IsWPHjqm6ulperzdivG3btlq7dq3jOU9E0Y1TWG1GdnwpdzTNy+xeDl7XkvOmopEaAAAAEJsCgYDy8vIixnJzc+X3+yPGOnTooCFDhuh3v/udzjvvPHXt2lVvvPGG1q1bpz59+rRgYopu1MFqM7LjxW00zcvsXg5e15LzpqKRGgAAABCbfD6fcnJyIsZOnuU+7g9/+IPuvPNOnX322UpKStKPf/xjjRs3TuvXr2+JqLUougG413dFphPAih4Xmk4Ai8Lffms6AiyikRpgr4STliAjdtW1lLw+vXr10urVq1VRUaFDhw4pPT1dt912m3r27OlwykiJLfo0AAAAAABaUPv27ZWenq6ysjK99957uummm1r0+cx0I+ZEs0fcDuzpBgAAANzvvffeUzgcVr9+/bR161Y99NBD6tevnyZNmiRJ2r9/v3bu3Knvv/9ekrR582ZJUlpamtLS0mzLQdGNmBPNHnFbns+ebgAAAMD1Dh48KJ/Pp927dyslJUW33HKLZsyYodatW0uSli1bVluAS9LYsWMl1d2YLRoU3QAAAACAuDNmzBiNGTOm3vcnTpyoiRMnOp6DohsA4KjwgWLTEWBRQq9epiPAovABe4/chDPCBZ+YjgCrzupoOgHiGI3UAAAAAABwCDPdiEvRNGOjkRoAAAAAu1B0Iy5F04yNRmoAAAAA7MLycgAAAAAAHMJMN1ypseXjJSU0mAFiRUJH+865hLPCletMR4BV3nLTCWBBuOKI6QiwKMF0AMQ1im64UmPLx6dMmdKCaQAAAACgbhTdMMrr9Z5SINsxS13Xfa2ikRoAAAAAu1B0w6hAIHDKmB2z1HXd1yoaqQEAAADxJRAI6JFHHtEDDzyg2bNnS5L8fr8WLVqkXbt2qU2bNho0aJBmzJihwYMH2/psim7EJPZsA/EjfKDYdARYFC4rMx0BFiWkdDYdARYknJNuOgKsKjtgOgEc9Nlnn2nevHm68MILI8b79u2rOXPm6Ec/+pGOHDmi/Px8jRgxQlu3blXnzvb9OUvRjZjEnm0AAAAA0SovL9cdd9yhl156SdOnT494b9y4cRGvn376ac2fP1+ff/65rrnmGtsycGQYAAAAAMAVQqGQDh06FPEVCoXqvf7ee+/VyJEjNXz48Abve/ToUc2bN0/JycnKysqyNTMz3Yg7jS1NbwyN1AAAAIDYFAgElJeXFzGWm5srv99/yrWLFi1SYWGhCgoK6r3f8uXLNXbsWFVWVio9PV0rVqxQp06dbM1M0Y2409jS9EY/TyM1AAAAICb5fD7l5OREjHk8nlOu27Vrlx544AG9//778nq99d5v2LBh2rhxo0pLS/XSSy9pzJgxWrdunbp06WJbZopuuFJDR4LRZO30EY5iRQNa0AF+T7pG27amE8CqtmeYTgALElJSTUeAReEjR0xHgEUej6fOIvtkhYWFKikp0aBBg2rHqqurtWbNGs2ZM0ehUEhJSUlq3769evfurd69e+uyyy5Tnz59NH/+fPl8PtsyU3TDlRo6EowmawAAAMDp7ZprrtGmTZsixiZNmqT+/fvr4YcfVlJSUp2fC4fDDe4Rbw6KbsSdhmbBrWBPNwAAAOBuHTp00IABAyLG2rdvr9TUVA0YMEAVFRWaMWOGbrzxRqWnp2vfvn16/vnntXv3bo0ePdrWLBTdiDler1c7d+5s9ucbmgW3gj3dAAAAQHxLSkrS119/rYULF6q0tFSpqam65JJL9NFHHykzM9PWZ1F0I+YEAgGWiAMAAACw1apVq2p/7PV6tXjx4hZ5LkU3mu34Mm4alwFoSKushs/FROyo+vYr0xFg1XdFphPAirN7mk4Ai8Kff2E6AuIYRTea7fgybmalAQAAAKBuFN1wJZ/Pp6BDx0XRSA0AAACAXSi64UrBYFD5+fnO3JtGagAAAABskmg6AAAAAAAA8YqZbgCulZBxrukIsCAcrDAdAVaVHTCdABaFz+poOgIsSKDhnWuEj4RMR0Aco+hGTDreGb0+dEwHAAAA4AYU3YhJxzuj16eugtyu5mo0UgMAAABgF4puxA27mqvRSA0AAABwvzVr1ujJJ59UYWGh9uzZoyVLlmjUqFG174fDYeXl5WnevHkqKyvT4MGD9dxzzykzM7P2mqFDh2r16tUR973tttu0aNEiyzkouuFKdS0/Z8k5EJvCIfZ0A3ajp4VLBCtNJ4BFiZ06mo4AB1RUVCgrK0uTJk3SLbfccsr7TzzxhJ5++mm9/PLL6tu3r6ZPn65rr71WmzdvVocOHWqvu+uuu/Tb3/629nXbtm2blIOiG65U1/LzhvaAAwAAADi9ZGdnKzs7u873wuGwZs+erUcffVQ333yzJGnhwoXq2rWrXn/9dd19992117Zr105paWnNzsGRYQAAAAAAVwiFQjp06FDEVyjU9O7zRUVFKi4u1ogRI2rHPB6Prr76an388ccR17722mvq1KmTMjMz9eCDD+rw4cNNehYz3YgbjXU8t4pGagAAAEBsCgQCysvLixjLzc2V3+9v0n2Ki4slSV27do0Y79q1q3bs2FH7+o477lDPnj2VlpamL774Qj6fT3/729+0YsUKy8+i6EbcaKzjuVU0UgMAAABik8/nU05OTsSYx+Np9v0SEhIiXofD4Yixu+66q/bHAwYMUJ8+fXTxxRdr/fr1+vGPf2zpGRTdANxr/z9MJ4AFNRtWmo4AxJ2a//1f0xFgwYEVNHl1izP6s+vWLdp5PFEV2ccd36NdXFys9PT02vGSkpJTZr9P9OMf/1itW7fWli1bLBfd/L8LAAAAAHBaOb5k/MRl4kePHtXq1at1+eWX1/u5L7/8UlVVVRGFemOY6QYAAAAAxJ3y8nJt3bq19nVRUZE2btyolJQUdevWTZMnT9bjjz+uPn36qE+fPnr88cfVrl07jRs3TpL07bff6rXXXtP111+vTp066e9//7v+4z/+QxdddJGuuOIKyzkouuE4n8+nYDBoOoZlNFIDAAAA3K+goEDDhg2rfX18L/iECRP08ssv69e//rWOHDmie+65R2VlZRo8eLDef//92jO627Rpo7/85S965plnVF5ernPPPVcjR45Ubm6ukpKSLOeg6IbjgsGg8vPzTcewjEZqAAAAgPsNHTpU4XC43vcTEhLk9/vr7Xx+7rnnavXq1VHnoOgG4FphF62gOJ0ltGtvOgIsqik9YDoCLErs1NF0BFhw1qjupiPAIv78g5NopAYAAAAAgEOY6T6NeL1eTZkypdHrSkpi93iLltgfzp5uAAAAAHah6D6NBAIBS9dZKcxNaYn94ezpBgAAAGAXlpcDAAAAAOAQZroBuFZCSqrpCLAg8bwhpiPAoup1haYjAAAQdyi6EROs7tWO5f3mAAAAAHAyim5ErbEGbVYKZat7tRt6jl1N1mikBgAAAMAuFN2IWmMN2lqqMZtdTdZopAYAAAC435o1a/Tkk0+qsLBQe/bs0ZIlSzRq1Kja9/1+vxYtWqRdu3apTZs2GjRokGbMmKHBgwfXXlNcXKyHHnpIK1as0OHDh9WvXz898sgjuvXWWy3noJEaAAAAACDuVFRUKCsrS3PmzKnz/b59+2rOnDnatGmT1q5dqx49emjEiBH6xz/+UXvN+PHjtXnzZi1btkybNm3SzTffrNtuu00bNmywnIOZbrhKQ0vZ2e99GqqsMJ0AFoSDh01HgEWJnTqajgCLakoPmI4ACxLP6Wo6Aiziz7/4lJ2drezs7HrfHzduXMTrp59+WvPnz9fnn3+ua665RpL0ySefaO7cubr00kslSY899pjy8/O1fv16XXTRRZZyUHTDVRpayh7L54sDAAAAiF4oFFIoFIoY83g88ng8Ud336NGjmjdvnpKTk5WVlVU7fuWVV+rNN9/UyJEj1bFjR/3Xf/2XQqGQhg4davneFN2IG401dLOKRmoAAABAbAoEAsrLy4sYy83Nld/vb9b9li9frrFjx6qyslLp6elasWKFOnXqVPv+m2++qdtuu02pqalq1aqV2rVrpyVLlqhXr16Wn0HRjbjRWEM3q2ikBgAAAMQmn8+nnJyciLFoZrmHDRumjRs3qrS0VC+99JLGjBmjdevWqUuXLpJ+WE5eVlamlStXqlOnTlq6dKlGjx6tjz76SBdccIGlZ1B0AwAcFT5AvwW3YJ+weyQNHmQ6AiwIf7fbdAQg7tixlPxE7du3V+/evdW7d29ddtll6tOnj+bPny+fz6dvv/1Wc+bM0RdffKHMzExJUlZWlj766CM999xzeuGFFyw9g+7lAAAAAABICofDtXvGKysrJUmJiZFlc1JSkmpqaizfk5luAAAAAEDcKS8v19atW2tfFxUVaePGjUpJSVFqaqpmzJihG2+8Uenp6dq3b5+ef/557d69W6NHj5Yk9e/fX71799bdd9+tp556SqmpqVq6dKlWrFih5cuXW85B0Q3HWWlwFs1xXz6fT8FgsNmfPxmN1AAAAAD3Kygo0LBhw2pfH98LPmHCBL3wwgv6+uuvtXDhQpWWlio1NVWXXHKJPvroo9ql5K1bt9bbb7+tqVOn6oYbblB5ebl69+6thQsX6vrrr7ecg6IbjrPS4CyaruPBYFD5+fnN/vwp96ORGgAAAOB6Q4cOVTgcrvf9xYsXN3qPPn366K233ooqB0U3APdK6Ww6AQCY4W1nOgEsqNm913QEWJTYqaPpCIhjFN2IeY0tH49maToAAAAAOImiGzGvseXj0SxNBwAAAAAnUXQj7kTbWI1GagAAAADsQtGNuBNtYzUaqQEAAACwC0U3XO/kI8nY430aCVaaTgALEtJ/ZDoCLKouPWw6AixK4s8/VwgfCZmOAKu8HtMJEMcouuF6Jx9Jxh5vAAAAALGCohtx5+SZ76ZiTzcAAAAAu1B0IyY0VCg3dbn4yTPfTcWebgAAAMD91qxZoyeffFKFhYXas2ePlixZolGjRtW+P3HiRC1cuDDiM4MHD9ann35qaw6KbsSEhgpllosDAAAAaKqKigplZWVp0qRJuuWWW+q85rrrrtOCBQtqX7dp08b2HBTdANzL2850AiCutO5/rukIsKqywnQCWHB0B/+d3MLTdq/pCHBAdna2srOzG7zG4/EoLS3N0RyJjt4dAAAAAACbhEIhHTp0KOIrFGr+SQGrVq1Sly5d1LdvX911112OnITETDdcxefzKRgMOvoMGqkBAAAAsSkQCCgvLy9iLDc3V36/v8n3ys7O1ujRo9W9e3cVFRVp2rRp+pd/+RcVFhbK47HvGDmKbrhKMBhUfn6+s8+gkRoAAAAQk3w+n3JyciLGmlsg33bbbbU/HjBggC6++GJ1795df/7zn3XzzTdHlfNEFN0AAAAAAFfweDy2zkKfKD09Xd27d9eWLVtsvS9FN2LeiceJObHHAi62/x+mE8CCcNszTEeARTWlB0xHgEVJFw8xHQGWfGw6ACxKPKer6QiIAfv27dOuXbuUnp5u630puhHzTjxOjOPDAAAAAFhRXl6urVu31r4uKirSxo0blZKSopSUFPn9ft1yyy1KT0/X9u3b9cgjj6hTp0762c9+ZmsOim64yomz3k6hkRoAAADgfgUFBRo2bFjt6+N7wSdMmKC5c+dq06ZNeuWVV3TgwAGlp6dr2LBhevPNN9WhQwdbc1B0w1VOnPV2Co3UAAAAAPcbOnSowuFwve+/9957LZKDohs4Sc2XBaYjwKKaLdtNR4AFra+4yXQEWHWd6QCw7Ei56QSw4IzZs0xHgEU1f/2T6QiIY4mmAwAAAAAAEK8ougEAAAAAcAjLy9EkPp9PwWDQdAxHzTjPdAIAAAAA8YKiG00SDAaVn59vOoajKudxLBkAAAAAe1B0A3CthLYe0xFgQfhAsekIQNwJf/uN6QiwoPr7XaYjAIgB7OkGAAAAAMAhFN0AAAAAADiE5eWISSYbttFIDQAAAHA3v9+vvLy8iLGuXbuquLi49v1FixZp165datOmjQYNGqQZM2Zo8ODBtmeh6EZMMtmwjUZqAAAAgPtlZmZq5cqVta+TkpJqf9y3b1/NmTNHP/rRj3TkyBHl5+drxIgR2rp1qzp37mxrDoputJimzF6XlJQ4nAYAcLJwwSemI8CqszqaTgALElJSTUeAReFvvzUdAQ5o1aqV0tLS6nxv3LhxEa+ffvppzZ8/X59//rmuueYae3PYejegAU2ZvZ4yhdlmAAAAAJFCoZBCoVDEmMfjkcdz6qk2W7ZsUUZGhjwejwYPHqzHH39cP/rRj0657ujRo5o3b56Sk5OVlZVle2aKbpzC6/XWW/S21Ax0Qxmcxp5uAAAAIDYFAoFT9mrn5ubK7/dHjA0ePFivvPKK+vbtq71792r69Om6/PLL9eWXXyo19YdVKMuXL9fYsWNVWVmp9PR0rVixQp06dbI9M0U3ThEIBOp9r6UK4YYyOI093QAAAEBs8vl8ysnJiRira5Y7Ozu79scXXHCBhgwZol69emnhwoW1nx82bJg2btyo0tJSvfTSSxozZozWrVunLl262JqZI8MAAAAAAK7g8Xh05plnRnzVVXSfrH379rrgggu0ZcuWiLHevXvrsssu0/z589WqVSvNnz/f9szMdANwrYTUjqYjwIKEjnU3MEHsSci8wHQEIK5Ur/7IdARYlNC28aIN7hYKhfTVV1/pJz/5Sb3XhMPhU/aL24GZbgAAAABAXHnwwQe1evVqFRUVad26dbr11lt16NAhTZgwQRUVFXrkkUf06aefaseOHVq/fr1+8YtfaPfu3Ro9erTtWZjpRkxryjFjdqGRGgAAAOBuu3fv1u23367S0lJ17txZl112mT799FN1795dwWBQX3/9tRYuXKjS0lKlpqbqkksu0UcffaTMzEzbs1B0I6Y15Zgxu9BIDQAAAHC3RYsW1fue1+vV4sWLWywLy8sBAAAAAHAIM91okmjOz26pM75x+qjZvdd0BFiQZDoArGt7hukEsCj87VemI8CC0Nf7TUeARW26tzcdAXGMohtNEs352ceL9abs06ZQBwAAAOBmFN1ocU3Zp93QrLpTTdZopAYAAADALhTdcC2nmqzRSA0AAACAXSi6AQCOSkzuYjoCLAp35L+VW4SPrDcdARa06tTadARYlNDWYzoC4hjdywEAAAAAcAgz3YhpDXVLp8kaAAAAgFhH0Y2Y1lC3dKearNFIDQAAAIBdKLoRl6JpskYjNQAAAMD91qxZoyeffFKFhYXas2ePlixZolGjRkmSqqqq9Nhjj+ntt9/Wtm3blJycrOHDh2vmzJnKyMiIuM8nn3yiRx99VOvWrVPr1q01cOBAvfPOO2rbtq2lHBTdcC2WniN8JGQ6AgCYYfEfejArqVMH0xFgUWKnjqYjwAEVFRXKysrSpEmTdMstt0S8V1lZqfXr12vatGnKyspSWVmZJk+erBtvvFEFBQW1133yySe67rrr5PP59Oyzz6pNmzb629/+psRE6+3RKLrhWs1deg4AAAAg/mVnZys7O7vO95KTk7VixYqIsWeffVaXXnqpdu7cqW7dukn6oa64//77NXXq1Nrr+vTp06QcdC9Hizk+M80sNAAAAIDmCIVCOnToUMRXKGTP6seDBw8qISFBHTt2lPTD6tl169apS5cuuvzyy9W1a1ddffXVWrt2bZPuy0w3WszxmemWmIVuaOl5Y2ikBgAAAMSmQCCgvLy8iLHc3Fz5/f6o7hsMBjV16lSNGzdOZ555piRp27ZtkiS/36+nnnpKAwcO1CuvvKJrrrlGX3zxheUZb4puxKWGlp43hkZqAAAAQGzy+XzKycmJGPN4PFHds6qqSmPHjlVNTY2ef/752vGamhpJ0t13361JkyZJki666CL95S9/0e9//3vLNQdFN3CS6s83m44AxJWag2wpcYvwAf5bucaRI6YTwIKk6+reS4rYU7P6A9MRYJHH44m6yD5RVVWVxowZo6KiIn3wwQe1s9ySlJ6eLkk6//zzIz5z3nnnaefOnZafwZ5uAAAAAMBp53jBvWXLFq1cuVKpqakR7/fo0UMZGRnavDlyUu6bb75R9+7dLT+HmW7EJJ/Pp2AwaOTZvzXyVAAAAAB2Ki8v19atW2tfFxUVaePGjUpJSVFGRoZuvfVWrV+/XsuXL1d1dbWKi4slSSkpKWrTpo0SEhL00EMPKTc3V1lZWRo4cKAWLlyor7/+Wv/93/9tOQdFN2JSMBhUfn6+kWcfvu96I88FAAAAYJ+CggINGzas9vXxveATJkyQ3+/XsmXLJEkDBw6M+NyHH36ooUOHSpImT56sYDCoKVOmaP/+/crKytKKFSvUq1cvyzkougEAAAAAcWfo0KEKh8P1vt/QeyeaOnVqxDndTUXRDQBwVGJyF9MRYFHY2950BFgUbtvWdARYUP3uO6YjwKLEc7qajoA4RtGNFmflDO2SEjroAgAAAHA/im60OCvn2TVUlDvdZI1GagAAAADsQtEN13G6yRqN1AAAAADYhaIbAOComoNsF3GL8J4i0xFgUYLXazoCLEjs1NF0BFhUs3uv6QiIY4mmAwAAAAAAEK+Y6UZMaqjZGk3WAAAAALgFRTdiUkPN1qZMmeJoMzUaqQEAAACwC0U3XMnJZmo0UgMAAADcb82aNXryySdVWFioPXv2aMmSJRo1apQkqaqqSo899pjefvttbdu2TcnJyRo+fLhmzpypjIyM2nvcfffdWrlypb7//nudccYZuvzyyzVr1iz179/fcg6KbriO1+vVzp07TcdADKipOGo6AixITO5iOgIsCvccYDoCLKopXG06Aqw4q6PpBLCq9IDpBHBARUWFsrKyNGnSJN1yyy0R71VWVmr9+vWaNm2asrKyVFZWpsmTJ+vGG29UQUFB7XWDBg3SHXfcoW7dumn//v3y+/0aMWKEioqKlJSUZCkHRTdcJxAINHiONwAAAABkZ2crOzu7zveSk5O1YsWKiLFnn31Wl156qXbu3Klu3bpJkn75y1/Wvt+jRw9Nnz5dWVlZ2r59u3r16mUpB0U3AAAAAMAVQqGQQqFQxJjH45HH44n63gcPHlRCQoI6duxY5/sVFRVasGCBevbsqXPPPdfyfSm64UoNdTePFo3UAAAAgNgUCASUl5cXMZabmyu/3x/VfYPBoKZOnapx48bpzDPPjHjv+eef169//WtVVFSof//+WrFihdq0aWP53hTdcKWGuptHi0ZqAAAAQGzy+XzKycmJGIt2lruqqkpjx45VTU2Nnn/++VPev+OOO3Tttddqz549euqppzRmzBj99a9/ldfrtXR/im7gJIcKnTmKDPbbX9zedARYcFWPEaYjwKKfdRpoOgIs2nbsgOkIsOCsxLamI8Cin4aTTUeARf/3SXuWkh9XVVWlMWPGqKioSB988MEps9zSD/u/k5OT1adPH1122WU666yztGTJEt1+++2WnkHRDQAAAAA47RwvuLds2aIPP/xQqamplj4XDodP2VfeEIruOODz+RQMMjtrlwdNBwAAAAAQtfLycm3durX2dVFRkTZu3KiUlBRlZGTo1ltv1fr167V8+XJVV1eruLhYkpSSkqI2bdpo27ZtevPNNzVixAh17txZ3333nWbNmqW2bdvq+uutb0ml6I4DwWBQ+fn5pmPEje+G/IvpCAAAAACiVFBQoGHDhtW+Pr4XfMKECfL7/Vq2bJkkaeDAgRGf+/DDDzV06FB5vV599NFHmj17tsrKytS1a1ddddVV+vjjj9WlSxfLOSi6AQAAAABxZ+jQoQqHw/W+39B7kpSRkaG333476hwU3QBcq0My2yrcoMeRrqYjwCKvEk1HgEU/atXRdARY8My/VpqOAIvefqvh4guIBn+7AgAAAADgEGa6TxM0W7OORmoAAAAA7ELRfZqg2Zp1NFIDAAAAYBeWlwMAAAAA4BBmugG4VijIH2FuMMx7rukIsCj7CI2E3OJ5T8h0BFjwn/9zlukIsOiqML+n4BxmugEAAAAAcAjTRGgRbmrkRiM1AAAAAHah6EaLcFMjNxqpAQAAAO7Wo0cP7dix45Txe+65R7Nnz9Zjjz2mt99+W9u2bVNycrKGDx+umTNnKiMjw/YsFN2nIROzziUlJS36PACxox07mVzjrNaVpiMAceXGxEOmI8CqtqYDwG6fffaZqqura19/8cUXuvbaazV69GhVVlZq/fr1mjZtmrKyslRWVqbJkyfrxhtvVEFBge1ZKLpPQyZmnadMmdKizwMAAABw+urcuXPE65kzZ6pXr166+uqrlZCQoBUrVkS8/+yzz+rSSy/Vzp071a1bN1uzUHQDAAAAAFwhFAopFIrsNu/xeOTxeOr9zNGjR/Xqq68qJydHCQkJdV5z8OBBJSQkqGPHjnbGlUTRjRbi9XpdM9tNIzUAAAAgNgUCAeXl5UWM5ebmyu/31/uZpUuX6sCBA5o4cWKd7weDQU2dOlXjxo3TmWeeaWPaH1B0o0UEAgHTESyjkRoAAAAQm3w+n3JyciLGGprllqT58+crOzu7ziZpVVVVGjt2rGpqavT888/bmvU4im4ArnXGWaHGL4JxhbvLTEeARb3DqaYjwLKDpgPAgr8H7Z8xgzNSao6ZjgCLLmhkKfnJduzYoZUrV2rx4sWnvFdVVaUxY8aoqKhIH3zwgSOz3BJFNwAAAAAgTi1YsEBdunTRyJEjI8aPF9xbtmzRhx9+qNRU577xTNENAAAAAIg7NTU1WrBggSZMmKBWrf5Z+h47dky33nqr1q9fr+XLl6u6ulrFxcWSpJSUFLVp08bWHBTdcaa+M7jddE62iXPET0QjNQAAAMD9Vq5cqZ07d+rOO++MGN+9e7eWLVsmSRo4cGDEex9++KGGDh1qaw6K7jhT3xncbukcLpk5R/xENFIDAAAA3G/EiBEKh8OnjPfo0aPOcadQdANwraojSaYjwIKvK783HQEWfXdGiukIsKis+ojpCLDgfK/pBLBq25EOpiMgjiWaDgAAAAAAQLxiphu2sWsvdkP7z1tivzd7ugEAAADYhaIbtrFrL3ZD+89bYr83e7oBAAAA2IXl5QAAAAAAOISZbgCu1bpttekIsMCTZO9Zl3DOvgR+T7nFWYltTUeABcWV7UxHgEVnt640HQFx7LQpuk2f/ewkN53BbYXX6613iXm8/VwBAAAAxLfTpug2ffazk9x0BrcVgUCg3vca+7na8c0VGqkBAAAAsMtpU3Tj9GDHN1dopAYAAAC435o1a/Tkk0+qsLBQe/bs0ZIlSzRq1Kja9/1+vxYtWqRdu3apTZs2GjRokGbMmKHBgwfXXnP33Xdr5cqV+v7773XGGWfo8ssv16xZs9S/f3/LOWikBgAAAACIOxUVFcrKytKcOXPqfL9v376aM2eONm3apLVr16pHjx4aMWKE/vGPf9ReM2jQIC1YsEBfffWV3nvvPYXDYY0YMULV1db7oDDTDVdpaL+3xJ5vIBZ1bNXedARYlBpOMh0BFhWZDgBLzmodMh0BFnla00gyHmVnZys7O7ve98eNGxfx+umnn9b8+fP1+eef65prrpEk/fKXv6x9v0ePHpo+fbqysrK0fft29erVy1IOim64SkP7vaX4298OAAAA4J9CoZBCochvaHk8Hnk8nqjue/ToUc2bN0/JycnKysqq85qKigotWLBAPXv21Lnnnmv53hTdiCuNzYRbQSM1AAAAIDYFAgHl5eVFjOXm5srv9zfrfsuXL9fYsWNVWVmp9PR0rVixQp06dYq45vnnn9evf/1rVVRUqH///lqxYoXatLF+JCpFN+JKYzPhVtBIDQAAAIhNPp9POTk5EWPRzHIPGzZMGzduVGlpqV566SWNGTNG69atU5cuXWqvueOOO3Tttddqz549euqppzRmzBj99a9/ldfrtfQMiu7TxIkzwOx7btiZg6z95oF5R3dUmI4AC/Z+c8B0BFj0XZsujV+EmHCxzjQdARYUJCSYjgCLhnn2mY4Ai+xYSn6i9u3bq3fv3urdu7cuu+wy9enTR/Pnz5fP56u9Jjk5WcnJyerTp48uu+wynXXWWVqyZIluv/12S8+g6D5NnDgDzL5nAAAAADhVOBw+Zc94c645EUU36uTz+RQMBpv0GWbQAQAAAMSK8vJybd26tfZ1UVGRNm7cqJSUFKWmpmrGjBm68cYblZ6ern379un555/X7t27NXr0aEnStm3b9Oabb2rEiBHq3LmzvvvuO82aNUtt27bV9ddfbzkHRTfqFAwGlZ+f36TPtNQMenO+IdAUv3XszgAAAABaSkFBgYYNG1b7+vhe8AkTJuiFF17Q119/rYULF6q0tFSpqam65JJL9NFHHykzM1PSD1t0P/roI82ePVtlZWXq2rWrrrrqKn388ccRe74bQ9EN12nONwSa4vB91r9rBQAAACA2DR06VOFwuN73Fy9e3ODnMzIy9Pbbb0edg6IbAABIkrxKNB0BFn2bYH0vIczxJtCc1S2OhiiL4Bz+dgUAAAAAwCF8SwdGRLMvm4ZtAAAAANyCohtGRLMvu76GbXY1WKORGgAAAAC7UHQjbtjVYI1GagAAAADsQtENAAAkSQd0zHQEWETTO3f4LpHfU27RxsN/KziHohuu4/V661xizl5vAAAAALGGohuuEwgE6hw/sRCPZn83e7oBAAAA2IWiG3Epmv3d7OkGAAAA3O3YsWPy+/167bXXVFxcrPT0dE2cOFGPPfaYEhN/2KKzePFivfjiiyosLNS+ffu0YcMGDRw40PYsFN0AAAAAgLgya9YsvfDCC1q4cKEyMzNVUFCgSZMmKTk5WQ888IAkqaKiQldccYVGjx6tu+66y7EsFN2IGyfu9WZ/9+khWJpkOgIs8CS1MR0BiDtB1ZiOAAtS+Ke2axwu95iOAJt98sknuummmzRy5EhJUo8ePfTGG2+ooKCg9prx48dLkrZv3+5oFv4kQNw4ca93fWd5AwAAAHCvUCikUCgUMebxeOTxRH7j5Morr9QLL7ygb775Rn379tXf/vY3rV27VrNnz27BtD+g6IZt6usqXhenZ6KbkuVkNFIDAAAAYlMgEFBeXl7EWG5urvx+f8TYww8/rIMHD6p///5KSkpSdXW1ZsyYodtvv70F0/6Aohu2qa+reF2cnoluSpaT0UgNAAAAiE0+n085OTkRYyfPckvSm2++qVdffVWvv/66MjMztXHjRk2ePFkZGRmaMGFCS8WVRNENAAAAAHCJupaS1+Whhx7S1KlTNXbsWEnSBRdcoB07digQCFB0o+loIIbTVftuYdMRYEHom6OmI8CijvyzwDXaKdF0BFjw0yB//rlFh46hxi+Cq1RWVtYeDXZcUlKSampavhElf7vGARqIAQAAAMA/3XDDDZoxY4a6deumzMxMbdiwQU8//bTuvPPO2mv279+vnTt36vvvv5ckbd68WZKUlpamtLQ027JQdCMm+Hw+BYNB0zEk0UgNAAAAcLtnn31W06ZN0z333KOSkhJlZGTo7rvv1m9+85vaa5YtW6ZJkybVvj6+FL2uxmzRoOg+DVnp7N3Sy9SDwaDy8/Nb9Jn1oZEaAAAA4G4dOnTQ7NmzGzwibOLEiZo4caLjWSi6T0NWOnuzTB1ukNAuyXQEWHDZGT1NR4BFfav5ZwFgp+8TGm/2hNjQRRWmIyCO0YUDAAAAAACH8C1tGHHyEne6rgMAAACIRxTdMOLkJe4NLWdv6SZrNFIDAAAAYBeKbsS8lm6yRiM1AAAAAHah6AbgWsHtVaYjwII91eWmI8CqhDNMJ4BF3yQdMx0BFvTln9oARNGNGNHQMWbs9wYAAADgVhTdiAkNHWPG8WUAAAAA3IqiG65nd6M1GqkBAAAA7nbs2DH5/X699tprKi4uVnp6uiZOnKjHHntMiYmJqqqq0mOPPaa3335b27ZtU3JysoYPH66ZM2cqIyPD1iwU3XA9uxut0UgNAAAAcLdZs2bphRde0MKFC5WZmamCggJNmjRJycnJeuCBB1RZWan169dr2rRpysrKUllZmSZPnqwbb7xRBQUFtmah6EbMa2i/t8Se79OZt0dr0xFgwcGvjpiOAKv4LeUa7ZRoOgIsOOtY2HQEWOTx0pww3nzyySe66aabNHLkSElSjx499MYbb9QW1MnJyVqxYkXEZ5599lldeuml2rlzp7p162ZbFopuxLyG9ntL7PkGAAAAThehUEihUChizOPxyOPxRIxdeeWVeuGFF/TNN9+ob9+++tvf/qa1a9dq9uzZ9d774MGDSkhIUMeOHW3NTNEN12tsJryp2NMNAAAAxKZAIKC8vLyIsdzcXPn9/oixhx9+WAcPHlT//v2VlJSk6upqzZgxQ7fffnud9w0Gg5o6darGjRunM88809bMFN1wvcZmwpuKPd0AAABAbPL5fMrJyYkYO3mWW5LefPNNvfrqq3r99deVmZmpjRs3avLkycrIyNCECRMirq2qqtLYsWNVU1Oj559/3vbMFN0AAAAAAFeoayl5XR566CFNnTpVY8eOlSRdcMEF2rFjhwKBQETRXVVVpTFjxqioqEgffPCB7bPcEkU3cIqkC/uZjgCLErZsNx0BFhQHvzcdARZ97j3bdARYdHaYrnduMDB5v+kIsOhvxZ1NR4BFPSxeV1lZqcTEyKaTSUlJqqmpqX19vODesmWLPvzwQ6WmptoX9AQU3QAAAACAuHLDDTdoxowZ6tatmzIzM7VhwwY9/fTTuvPOOyX9cI73rbfeqvXr12v58uWqrq5WcXGxJCklJUVt2rSxLQtFN2zh8/kUDAZNx7DFjPNMJwAAAAAQjWeffVbTpk3TPffco5KSEmVkZOjuu+/Wb37zG0nS7t27tWzZMknSwIEDIz774YcfaujQobZloeiGLYLBoPLz803HsEXlPI4gAwAAANysQ4cOmj17dr1HhPXo0UPhcLhFsiQ2fgkAAAAAAGgOZrpRp6aefV1SUuJgmpZV/flm0xFgUU3FUdMRYEGa9yzTEWDRnpojpiPAotuP1jR+EYw7XN14h2XEhv4dy0xHQByj6Eadmnr2dVMKdAAAAAA4XVB0wxZNnRmPZb81HQAAAABA3KDohi2aOjMeyw7fd73pCAAAAADiBEU3cJKkC/uZjgCLko6w/9QNevzlO9MRYNHEox1MR4BF3ybRC9cNPm91zHQEWHTh4TNMR4BFbvyXOn9iAwAAAADgEIpuAAAAAAAcwvLy04TP51MwGDQdwxVmnGc6AQAAAAA7BQIBPfLII3rggQc0e/ZsSdLevXv18MMP6/3339eBAwd01VVX6dlnn1WfPn1sfTZF92kiGAwqPz/fdAxXqJwXH13YAQAAAEifffaZ5s2bpwsvvLB2LBwOa9SoUWrdurX+9Kc/6cwzz9TTTz+t4cOH6+9//7vat29v2/MpuoGTVH++2XQEIK78T/HfTEeARRs7dDIdARb9wjPAdARYUFRTYToCLBpcc6bpCHBIeXm57rjjDr300kuaPn167fiWLVv06aef6osvvlBmZqYk6fnnn1eXLl30xhtv6Be/+IVtGdjTDQAAAABwhVAopEOHDkV8hUKheq+/9957NXLkSA0fPvyU+0iS1+utHUtKSlKbNm20du1aWzMz0x1nvF6vpkw5dXl0SUlJk+5zOu8B/63pAAAAAADqFAgElJeXFzGWm5srv99/yrWLFi1SYWGhCgoKTnmvf//+6t69u3w+n1588UW1b99eTz/9tIqLi7Vnzx5bM1N0x5lAIFDneF2FeENO5z3gh++73nQEAAAAAHXw+XzKycmJGPN4PKdct2vXLj3wwAN6//33I2azj2vdurXeeust/fznP1dKSoqSkpI0fPhwZWdn256ZohsAAAAA4Aoej6fOIvtkhYWFKikp0aBBg2rHqqurtWbNGs2ZM0ehUEiDBg3Sxo0bdfDgQR09elSdO3fW4MGDdfHFF9uamaIbOEnShf1MR4BF4d32Lv2BMzq0aWs6Aiz6WQfOTHSNsOkAsOLiBJpzuUVKzTHTEWCza665Rps2bYoYmzRpkvr376+HH35YSUlJtePJycmSfmiuVlBQoN/97ne2ZqHoBgAAAADElQ4dOmjAgMiTHtq3b6/U1NTa8T/+8Y/q3LmzunXrpk2bNumBBx7QqFGjNGLECFuzUHSfJuprsFafpjZeO5mbG7HNYKIHAAAAiHt79uxRTk6O9u7dq/T0dP3bv/2bpk2bZvtzKLpPE/U1WKtPUxuvnczNjdgq50X3cwcAAAAQe1atWhXx+v7779f999/v+HM5pxsAAAAAAIcw0w3AtRJSO5qOAMSVA6KRkFtkB+mk5gbvtE0wHQEWnf+jf5iOgDhG0Y06NXUP+Mmi3RMOAAAAAPGAoht1auoe8JM1t2CPhQZsNFIDAAAAYBeKbsSUWGjARiM1AAAAAHah6IYjmrs8nWXpaIqa3XtNR4AFHT3tTUeARWU1IdMRYNG3bZJNR4AFRTUHTUeARd5O1aYjII5RdMMRzV2eHu1RZQAAAAAQSzgyDAAAAAAAhzDTjZgSbdd0O9BIDQAAAIBdKLoRU6Ltmm4HGqkBAAAA7ub3+5WXlxcx1rVrVxUXF9e+/uqrr/Twww9r9erVqqmpUWZmpv7rv/5L3bp1szULRTdwkrIFfzMdARbtL6ZBlxus7ZtqOgIsqzAdABb9z24aqblBforZY1BhXbA0yXQEOCAzM1MrV66sfZ2U9M//zt9++62uvPJK/fznP1deXp6Sk5P11Vdfyev12p6DohsAAAAAEHdatWqltLS0Ot979NFHdf311+uJJ56oHfvRj37kSA4aqQEAAAAAXCEUCunQoUMRX6FQ3UdebtmyRRkZGerZs6fGjh2rbdu2SZJqamr05z//WX379tVPf/pTdenSRYMHD9bSpUsdycxMN4zx+XwKBmNv2dWDpgMAAAAAqFMgEDhlr3Zubq78fn/E2ODBg/XKK6+ob9++2rt3r6ZPn67LL79cX375paqqqlReXq6ZM2dq+vTpmjVrlt59913dfPPN+vDDD3X11VfbmpmiG8YEg0Hl5+ebjnGK74b8i+kIAAAAAOrg8/mUk5MTMebxeE65Ljs7u/bHF1xwgYYMGaJevXpp4cKFGjt2rCTppptuqj05aeDAgfr444/1wgsvUHQjdkQ7U11SUmJjGvucOcj+5glwRqsvD5mOAAuOBWlO4xZn9GfXmVukF9WYjgDEFW+natMRYJHH46mzyG5M+/btdcEFF2jLli3q1KmTWrVqpfPPPz/imvPOO09r1661K2otim40W7Qz1abP4wYAAABwegiFQvrqq6/0k5/8RG3atNEll1yizZs3R1zzzTffqHv37rY/m6Ibxni93pgsvH9rOgAAAACAqDz44IO64YYb1K1bN5WUlGj69Ok6dOiQJkyYIEl66KGHdNttt+mqq67SsGHD9O677+p//ud/tGrVKtuzUHTDmEAgYDpCnQ7fd73pCAAAAACisHv3bt1+++0qLS1V586dddlll+nTTz+tncn+2c9+phdeeEGBQED333+/+vXrp7feektXXnml7VkougEAAAAAcWXRokWNXnPnnXfqzjvvdDwLRTcA1/J0oemTG5T8b3vTEWDRnl00vXOL1V4aqbnBleceNR0BFpVuaWc6AixKNR2gGSi6Xc7kWdex2n0cAAAAAGIFRbfLmTzrurlN0Ex+o8AKGqkBAAAAsAtFN1qcyW8UWEEjNQAAAAB2sbXojtUjoCSWQgMAAAAAWp6tRXesHgElNX8pNIDYVV1JIyE3+HvwTNMRYFFGOGQ6Aizqm8BiRTegOZd7dOpTaToC4hh/YqPZmruygVUHAAAAAE4XFN1otuaubGisUDfdaI1GagAAAADsQtGNmGO60RqN1AAAAAD3O3z4sKZNm6YlS5aopKREF110kZ555hldcsklkqTy8nJNnTpVS5cu1b59+9SjRw/df//9+vd//3dbc1B0A3CtVp1am44AC1JqjpmOAIuCSjIdARb1OlplOgIs6DSQfcKASb/4xS/0xRdf6A9/+IMyMjL06quvavjw4fr73/+us88+W1OmTNGHH36oV199VT169ND777+ve+65RxkZGbrppptsy5Fo250AAAAAAIgBR44c0VtvvaUnnnhCV111lXr37i2/36+ePXtq7ty5kqRPPvlEEyZM0NChQ9WjRw/98pe/VFZWlgoKCmzNwkw3WlxjDdhotAYAAACgLqFQSKFQ5GkbHo9HHo8nYuzYsWOqrq6W1+uNGG/btq3Wrl0rSbryyiu1bNky3XnnncrIyNCqVav0zTff6JlnnrE1M0U3WlxjDdisdER3stkajdQAAACA2BQIBJSXlxcxlpubK7/fHzHWoUMHDRkyRL/73e903nnnqWvXrnrjjTe0bt069enTR5L0n//5n7rrrrt0zjnnqFWrVkpMTNT/+3//T1deeaWtmSm64UpONlujkRoAAAAQm3w+n3JyciLGTp7lPu4Pf/iD7rzzTp199tlKSkrSj3/8Y40bN07r16+X9EPR/emnn2rZsmXq3r271qxZo3vuuUfp6ekaPny4bZkpuhFzrJz/zRJ0SFJwO42E3OCs1qHGLwLQJN9WtzcdARbQ8NM9jpXybwq3qGspeX169eql1atXq6KiQocOHVJ6erpuu+029ezZU0eOHNEjjzyiJUuWaOTIkZKkCy+8UBs3btRTTz1F0Y34ZuX8bytL0AEAAACgffv2at++vcrKyvTee+/piSeeUFVVlaqqqpSYGNlbPCkpSTU1NbY+n6IbAAAAABB33nvvPYXDYfXr109bt27VQw89pH79+mnSpElq3bq1rr76aj300ENq27atunfvrtWrV+uVV17R008/bWsOim64kpUl6M1FIzUAAADA/Q4ePCifz6fdu3crJSVFt9xyi2bMmKHWrX/Y+rFo0SL5fD7dcccd2r9/v7p3764ZM2bo//7f/2trDopuuJKVJejNRSM1AAAAwP3GjBmjMWPG1Pt+WlqaFixY4HgOim7gJEkX9jMdARZ16HPEdARY0GfjVtMRYFHZhgTTEWBRn4vKTUeABave6WI6Aiy6Zjz/poBzEhu/BAAAAAAANAcz3Qb4fD4Fg0Fb7tXco7PszBBvZpxnOgEAAACAeEHRbUAwGFR+fr4t92puMzE7M8SbynkcRwYAAADAHiwvBwAAAADAIcx0AydJzLzYdARYFN5TZDoCLHjjKRo+ucVZx8KmI8Ci67TXdARYcO1vu5qOAIuO/mWj6QiIY8x0AwAAAADgEGa6EbV4a8oWuJWZbgAAAAD2oOhG1OKtKVvwr6+ZjgAAAAAgCn6/X3l5eRFjXbt2VXFxsSQpISGhzs898cQTeuihh2zNQtENAAAAAIg7mZmZWrlyZe3rpKSk2h/v2bMn4tp33nlHP//5z3XLLbfYnoOiG4B7ndXFdAJYcHG4wHQEWJXU+CWIDa2HXGA6Aiyo2bLddARY1LofTe/iUatWrZSWllbneyeP/+lPf9KwYcP0ox/9yPYcNFIDAAAAALhCKBTSoUOHIr5CoVCd127ZskUZGRnq2bOnxo4dq23bttV53d69e/XnP/9ZP//5zx3JzEw34l5TG73RSA0AAACITYFA4JS92rm5ufL7/RFjgwcP1iuvvKK+fftq7969mj59ui6//HJ9+eWXSk1Njbh24cKF6tChg26++WZHMlN0I+41tdEbjdQAAACA2OTz+ZSTkxMx5vF4TrkuOzu79scXXHCBhgwZol69emnhwoWnfP73v/+97rjjDnm9XkcyU3SjTk2ZHS4pKXHs3nZoaj64R4K3vekIQFw5cox/FrhFQkpq4xchBmw3HQAWhY/UvTwZscfj8dRZZDemffv2uuCCC7Rly5aI8Y8++kibN2/Wm2++aVfEU/C3K+rUlNnhKVOmOHZvOzQ1HwAAAID4EgqF9NVXX+knP/lJxPj8+fM1aNAgZWVlOfZsGqkBAAAAAOLKgw8+qNWrV6uoqEjr1q3TrbfeqkOHDmnChAm11xw6dEh//OMf9Ytf/MLRLMx0I+55vd4mzXbTSA0AAABwt927d+v2229XaWmpOnfurMsuu0yffvqpunfvXnvNokWLFA6HdfvttzuahaIbcS8QCDTpehqpAQAAAO62aNGiRq/55S9/qV/+8peOZ6HoBuBa4bK9piPAgvRzD5mOAMSd8Lffmo4AC2jO5R5J53Y1HQFxjD3dAAAAAAA4hKIbAAAAAACHsLzc5ZraJOw4O8+ubmoGq89u6fO8j6ORGgAAAAC7UHS7XFObhB1n59nVTc1g9dktfZ537XNppAYAAADAJhTdMKqh2Ww7Z+MRp/b/w3QCWLBn15mmI8Aimt65R/UuGkm6wdEdFaYjwCJP2wOmIyCOUXTDqIZms+2cjQcAAAAAEyi6EbOau189WuzpBgAAAGAXim7ErObuV48We7oBAAAAdwsEAlq8eLG+/vprtW3bVpdffrlmzZqlfv361V6zePFivfjiiyosLNS+ffu0YcMGDRw40PYsHBkGAAAAAIgrq1ev1r333qtPP/1UK1as0LFjxzRixAhVVPyz10JFRYWuuOIKzZw509EszHSjxZ24bJxmaYjK2T1NJ4AF31bvNB0BFnUoC5mOAIu8NOhyBU//FNMRYFF16WHTEWCzd999N+L1ggUL1KVLFxUWFuqqq66SJI0fP16StH37dkezUHSjxZ24bJxmaQAAAACsCoVCCoUiv0ns8Xjk8Xga/NzBgwclSSkpLf/NMIpuxKyGjhNzEo3UAAAAgNgUCASUl5cXMZabmyu/31/vZ8LhsHJycnTllVdqwIABDic8FUU3YlZDx4k5+lwaqQEAAAAxyefzKScnJ2KssVnu++67T59//rnWrl3rZLR6UXQDAAAAAFzBylLyE/3qV7/SsmXLtGbNGp1zzjkOJqsfRTeMaugsbpqsoVFl/H/EDc73HjIdARYdLrf+jxiYldapynQEWJDQlt9TbpHUyXQC2C0cDutXv/qVlixZolWrVqlnT3MNeCm6YVRDZ3HTZA0AAABAc9x77716/fXX9ac//UkdOnRQcXGxJCk5OVlt27aVJO3fv187d+7U999/L0navHmzJCktLU1paWm2ZaHoRsxqaBbcSTRSAwAAANxt7ty5kqShQ4dGjC9YsEATJ06UJC1btkyTJk2qfW/s2LGSGm/M1lQU3YhZDc2CO4lGagAAAIC7hcPhRq+ZOHFibQHuJIpuAICjet7KXzVu8d3/tPwxjUA8C27YYzoCLEpql2g6AuIY/+8CAAAAAMAhFN0AAAAAADiENX+IOT6fT8GguSWONFIDAAAAYBeK7tNUY53BTZ6RHQwGlZ+fb+75NFIDAAAAYBOK7tNUY53BOSMbrnBWF9MJYEFFwX7TEWDRGWclmY4Ai46VVpuOAAu+/+JM0xFgUcaAQ6YjII5RdKNFNGXJuMlZdgAAAACwE0U3WkRTlowzyw4AAAAgXlB0w5WcbLZGIzUAAADA3ebOnau5c+dq+/btkqTMzEz95je/UXZ29inX3n333Zo3b57y8/M1efJk27NQdMOVnGy2RiM1AAAAwN3OOecczZw5U71795YkLVy4UDfddJM2bNigzMzM2uuWLl2qdevWKSMjw7EsFN2IOY11VpfY943/Txn/P3ADb4/WpiPAomOlVaYjwKJWnfh95QZtPMdMR4BF/J6KPzfccEPE6xkzZmju3Ln69NNPa4vu7777Tvfdd5/ee+89jRw50rEsFN2IOY11VpfY9w0AAACcjkKhkEKhUMSYx+ORx+Op9zPV1dX64x//qIqKCg0ZMkSSVFNTo/Hjx+uhhx6KmPl2AkU3XMnKbHhzsacbAAAAiE2BQEB5eXkRY7m5ufL7/adcu2nTJg0ZMkTBYFBnnHGGlixZovPPP1+SNGvWLLVq1Ur333+/45kpuuFKVmbDm4s93QAAAEBs8vl8ysnJiRirb5a7X79+2rhxow4cOKC33npLEyZM0OrVq3XkyBE988wzWr9+vRISEhzPTNGNZmlq93D2YAMAAACIVmNLyU/Upk2b2kZqF198sT777DM988wzOu+881RSUqJu3brVXltdXa3/+I//0OzZs2s7ntuFohvN0tTu4ezBhhPC+/eZjgALaM7lHn//rLPpCLCo73n/MB0BFqQNMZ0AViV16mA6AlpAOBxWKBTS+PHjNXz48Ij3fvrTn2r8+PGaNGmS7c+l6AYAAAAAxJVHHnlE2dnZOvfcc3X48GEtWrRIq1at0rvvvqvU1FSlpqZGXN+6dWulpaWpX79+tmeh6EbMaerSdbvRSA0AAABwt71792r8+PHas2ePkpOTdeGFF+rdd9/Vtdde2+JZKLoRc5q6dN3259NIDQAAAHC1+fPnN+l6u/dxn4iiG4BrJXi9piPAgmBpkukIsKhtq2OmI8CiA3vamY4AC9J60NPCLUJf7zcdARadYTpAMySaDgAAAAAAQLxiphstwuv1Wu5gzvFiAAAAAOIFRTdaRCAQsHxtQ8V5SzRZo5EaAAAAALtQdMNVWqLJGo3UAAAAANiFohsAAEiS0s89ZDoCEFeSOiWbjgCLwpUHTEdAHKPoRsxpaP83+70BAAAAuAlFN2JOQ/u/rTZjAwAAAIBYQNEN13KqqRqN1AAAAAD3W7NmjZ588kkVFhZqz549WrJkiUaNGlX7/uLFi/Xiiy+qsLBQ+/bt04YNGzRw4MDa97dv366ePXvWee//+q//0ujRoy3loOiGaznVVI1GagAAAID7VVRUKCsrS5MmTdItt9xS5/tXXHGFRo8erbvuuuuU988991zt2bMnYmzevHl64oknlJ2dbTkHRTdc5cT93uzvhs6u+zuPiDXrTAcAACOqSw+bjgCLKnYmmI4Aizo24drs7OwGi+Px48dL+mFGuy5JSUlKS0uLGFuyZIluu+02nXHGGZZzUHTDVU7c783+bgAAAOD0EgqFFAqFIsY8Ho88Ho/jzy4sLNTGjRv13HPPNelzFN1wrYa6nEeDPd0AAABAbAoEAsrLy4sYy83Nld/vd/zZ8+fP13nnnafLL7+8SZ+j6IZrNdTlPBrs6QYAAABik8/nU05OTsRYS8xyHzlyRK+//rqmTZvW5M9SdKNOjc0is58aAAAAQEtrqaXkJ/vv//5vVVZW6t/+7d+a/FmKbtSpsVlk9lMjJnxXZDoBLCgoSmv8IsSEduFq0xFgUZ/0/aYjwIJjpUdNR4BF7bslmo6AGDd//nzdeOON6ty5c5M/S9ENAAAAAIg75eXl2rp1a+3roqIibdy4USkpKerWrZv279+vnTt36vvvv5ckbd68WZKUlpYW0bV869atWrNmjd5+++1m5aDohqv5fD4Fg0Fb70kjNQAAAMD9CgoKNGzYsNrXx/eCT5gwQS+//LKWLVumSZMm1b4/duxYSac2Zvv973+vs88+WyNGjGhWDopuuFowGFR+fr6996SRGgAAAOB6Q4cOVTgcrvf9iRMnauLEiY3e5/HHH9fjjz/e7BxsXgAAAAAAwCHMdANwr5SmN7JAy0vRFtMRYNH3iS3fDRaIZ6Vb2pmOAIs69ak0HQFxjKIbjnBir3VdOLoMAAAAQCw7bYruxs6dbkmnQ6HoxF7rujT037S5hT+N1AAAAADY5bQpuhs7d7olxUrxH++aW/jTSA0AAACAXU6bohvxqaEVDKfDioLT3v5/mE4AxJWUmmOmIwBxxePl9xQAim64XEMrGFhRAAAAAMA0jgwDAAAAAMAhzHQjbjW3eR6N1AAAAADYhaIbcau5zfNopAYAAAC435o1a/Tkk0+qsLBQe/bs0ZIlSzRq1Kja98PhsPLy8jRv3jyVlZVp8ODBeu6555SZmRlxn08++USPPvqo1q1bp9atW2vgwIF655131LZtW0s5KLqBk9R8WWA6Aiyq/nyz6Qiw4NukFNMRYNGAhHLTEWBRaWl70xFgwfm/Ost0BFhU9fUu0xHggIqKCmVlZWnSpEm65ZZbTnn/iSee0NNPP62XX35Zffv21fTp03Xttddq8+bN6tChg6QfCu7rrrtOPp9Pzz77rNq0aaO//e1vSky0vlObohsAAAAAEHeys7OVnZ1d53vhcFizZ8/Wo48+qptvvlmStHDhQnXt2lWvv/667r77bkk/NGe+//77NXXq1NrP9unTp0k5aKQGAAAAAHCFUCikQ4cORXyFQqEm36eoqEjFxcUaMWJE7ZjH49HVV1+tjz/+WNIPRxCvW7dOXbp00eWXX66uXbvq6quv1tq1a5v0LGa60SyNNSlz4oxsn8+nYDBo+31PNuM8xx8BAAAAoBkCgYDy8vIixnJzc+X3+5t0n+LiYklS165dI8a7du2qHTt2SJK2bdsmSfL7/Xrqqac0cOBAvfLKK7rmmmv0xRdfWJ7xpuhGszTWpMyJM7KDwaDy8/Ntv+/JKudxvjcAAAAQi3w+n3JyciLGPB5Ps++XkJAQ8TocDteO1dTUSJLuvvtuTZo0SZJ00UUX6S9/+Yt+//vfW27cTNENwLUSU840HQEWnFVdYzoCLDrCPwtco22rY6YjwAKac7nHsdIq0xFgkcfjiarIPi4tLU3SDzPe6enpteMlJSW1s9/Hx88///yIz5533nnauXOn5WfxtytahB1Lw51Ysg4AAADg9NOzZ0+lpaVpxYoVuuiiiyRJR48e1erVqzVr1ixJUo8ePZSRkaHNmyNPzPnmm2/qbdBWF4putAg7lobXt2Td7r3e7OkGAAAA3K+8vFxbt26tfV1UVKSNGzcqJSVF3bp10+TJk/X444+rT58+6tOnjx5//HG1a9dO48aNk/TD0vOHHnpIubm5ysrK0sCBA7Vw4UJ9/fXX+u///m/LOSi64Xp27/VmTzcAAADgfgUFBRo2bFjt6+N7wSdMmKCXX35Zv/71r3XkyBHdc889Kisr0+DBg/X+++/XntEtSZMnT1YwGNSUKVO0f/9+ZWVlacWKFerVq5flHBTdAAAAAIC4M3ToUIXD4XrfT0hIkN/vb7Tz+dSpUyPO6W4qim64Rn3HlLHX+/SVkNrRdARYsKd1uekIsOjsMM253KKsKvomQnBeYvujpiPAKhqpwUEU3XCN+lryO3E8GQAAAADYgaIbrlffDHhz0UgNAAAAgF0ouuF6Vg+lt4pGagAAAADskmg6AAAAAAAA8YqZbjji5CXfNDsDTl8/673LdARYtGvLWaYjwKIfX1psOgIsOFSYZDoCLGrfjblIOIeiG444eck3zc4AAAAAnI4oumGMz+dTMBg0HeMUNFIDAAAAYBeKbhgTDAaVn59vOsYpaKQGAAAAuFuPHj20Y8eOU8bvuecePffcc1q8eLFefPFFFRYWat++fdqwYYMGDhzoSBaKbgCuFd53wHQEWNDqDNMJYJWndbXpCLCoaAP7792g36ijpiPAosovK0xHgM0+++wzVVf/8++1L774Qtdee61Gjx4tSaqoqNAVV1yh0aNH66677nI0C0U3AAAAACCudO7cOeL1zJkz1atXL1199dWSpPHjx0uStm/f7ngWim4AAAAAgCuEQiGFQqGIMY/HI4/HU+9njh49qldffVU5OTlKSEhwOuIpKLoRM2KlsRqN1AAAAIDYFAgElJeXFzGWm5srv99f72eWLl2qAwcOaOLEic6GqwdFN1rEyed2S6ee3R0rjdVopAYAAADEJp/Pp5ycnIixhma5JWn+/PnKzs5WRkaGk9HqRdGNFnHyud0SZ3cjegnnpJuOAAu+/wPNadyijeeY6QiwKFSVZDoCLPh+Zdh0BFiUNqS16QiwqLGl5CfbsWOHVq5cqcWLFzuYqmGJxp4MAAAAAICDFixYoC5dumjkyJHGMjDTDQAAAACIOzU1NVqwYIEmTJigVq0iS9/9+/dr586d+v777yVJmzdvliSlpaUpLS3N1hwU3YgbdjVio5EaAAAA4H4rV67Uzp07deedd57y3rJlyzRp0qTa12PHjpXUeFO25qDoRtywqxEbjdQAAAAA9xsxYoTC4bp7K0ycOLHFuplTdANwryNHTCeABTTnAuznaV1tOgIs6JheaToCLApX0uoKzqHohjEnHyN28hFiJ2ts+XhjnwcAAACAlkbRDWNOPkassSPEGls+bvUIssaKd/Z0AwAAALALRTdOO40V7+zpBgAAAGAXNi8AAAAAAOAQZroRN07eI14f9n7HkWDIdAIAMIIGhYC9EtolmY6AOEbRjbhx8h7x+ljd+w0AAAAA0aLoxmmnsRlxGqkBAAAAsAtFN2JGY8WwXcvCG5sRp5EaAAAA4H5r1qzRk08+qcLCQu3Zs0dLlizRqFGjJElVVVV67LHH9Pbbb2vbtm1KTk7W8OHDNXPmTGVkZNTeY968eXr99de1fv16HT58WGVlZerYsWOTclB0I2Y0VgyzLBwAAACAVRUVFcrKytKkSZN0yy23RLxXWVmp9evXa9q0acrKylJZWZkmT56sG2+8UQUFBRHXXXfddbruuuvk8/malYOiG4Br1ZQeMB0BFhwu95iOAIs6nEFzQrfYWXam6QiwIG1IlekIsKj86xrTEWBRchOuzc7OVnZ2dt33SU7WihUrIsaeffZZXXrppdq5c6e6desmSZo8ebIkadWqVc1I+wOKbgAAAACAK4RCIYVCkd8k9ng88nii/yb/wYMHlZCQ0OTl442h6IZr+Xw+BYNB2+9LIzUAAAAgNgUCAeXl5UWM5ebmyu/3R3XfYDCoqVOnaty4cTrzTHtXE1F0w7WCwaDy8/Ntvy+N1AAAAIDY5PP5lJOTEzEW7Sx3VVWVxo4dq5qaGj3//PNR3asuFN0AXCuhLXuF3eDIsWOmI8Ci9LMOmY4Ai84qZ/+9GxwrZU+3W7Tvlmg6Aiyyayn5cVVVVRozZoyKior0wQcf2D7LLVF0AwAAAABOQ8cL7i1btujDDz9UamqqI8+h6IZrnHyOt13ndgMAAACIP+Xl5dq6dWvt66KiIm3cuFEpKSnKyMjQrbfeqvXr12v58uWqrq5WcXGxJCklJUVt2rSRJBUXF6u4uLj2Pps2bVKHDh3UrVs3pfz/27vz6CjLu//jn5mQhUAIhJAQFAIR2UF51EYRgSC7aIWKiCDE2FqKAhJAiFRJnicQQQsRrVK2BGgVoQTbCLIou5SiLEIFEQGDIpF9zQJk5vcHNT8m64iTXDPD+3VOzmHu+07yOec64Z7vXPf1vUJCnMpB0Q2PUXQf75L27XZFczUaqQEAAACe7/PPP1dMTEzh65/Wgg8ZMkSJiYn65z//KUm68847Hb5v3bp16tSpkyRp5syZDo3bOnToIElKS0tTbGysUzkouuFVXNFcjUZqAAAAgOfr1KmT7HZ7qefLOveTxMTEX9wZnaIbHqvo4+YSj5zfbCy1a5qOACdUrZJtOgKcdPEMzQkBV6oS6ms6ApxkzykwHQFejKIbHqvo4+ZSyY+cAwAAAIAp9MYHAAAAAKCCMNMNr1LSI+c/F43UAAAAALgKRTe8SkmPnP9cNFIDAAAA4CoU3UARvn2Hm44AJxXs/5fpCHDC87bZpiPASbUuVTUdAU7KSL3bdAQ4YfNze0xHgJPqBuaYjgAn1TQd4AawphsAAAAAgArCTLebSUhIUF5enukYN7WpE5jpBgAAAOAaFN1uJi8vT9OnTzcd46Z25eQh0xEAAAAA/EIbN27Ua6+9pu3bt+vYsWNatmyZHn300cLziYmJWrRokb777jv5+fnprrvu0qRJkxQdHV14TX5+vsaMGaP33ntPubm5evDBB/X222/r1ltvdToHj5cDAAAAALzOpUuXdMcdd+itt94q8XyTJk301ltvac+ePdq8ebMaNmyobt266cSJE4XXvPDCC1q2bJkWLVqkzZs36+LFi+rdu7cKCgqczsFMN1DElYw3TUeAk+zfHzMdAU5o5FvTdAQ4qaOtuukIcNKEMf8xHQFOSP6/eqYjwEm5mTtMR0AF6Nmzp3r27Fnq+SeffNLh9bRp0zR37lzt3r1bDz74oM6dO6e5c+dq4cKF6tKliyTpr3/9q+rXr6+PP/5Y3bt3dyoHM90AAAAAAI+Qn5+v8+fPO3zl5+f/4p97+fJlzZo1S8HBwbrjjjskSdu3b9eVK1fUrVu3wuvq1aunVq1aacuWLU7/bGa6Ua6brbnbpOamEwAAAAAoSUpKipKSkhyOTZw4UYmJiTf08z788EM98cQTysnJUUREhNasWaPQ0FBJUnZ2tvz8/FSrVi2H7wkPD1d2drbTv4OiG+W62Zq75cwaZToCAAAAgBIkJCQoPj7e4Zi/v/8N/7yYmBjt2rVLJ0+e1OzZs/X444/r3//+t8LCwkr9HrvdLovF4vTv4PFyAAAAAIBH8Pf3V40aNRy+fknRXa1aNTVu3Fj33nuv5s6dqypVqmju3LmSpLp16+ry5cs6c+aMw/ccP35c4eHhTv8OZroBeCxLtaqmI8AJxwpOmo4AJ31fJdB0BDjpyas3z7IvT2YJqW06ApzkE8hcJK6x2+2Fa8Tvuusu+fr6as2aNXr88cclSceOHdN//vMfTZ061emfSdHtZSpi/fXx48dd+vMAAAAAoKJdvHhR33zzTeHrw4cPa9euXQoJCVHt2rU1adIkPfLII4qIiNCpU6f09ttv6/vvv1e/fv0kScHBwXrmmWc0evRo1a5dWyEhIRozZoxat25d2M3cGRTdXqYi1l+PGnVja5w9tQEbjdQAAAAAz/f5558rJiam8PVPa8GHDBmimTNn6quvvtL8+fN18uRJ1a5dW/fcc482bdqkli1bFn7P9OnTVaVKFT3++OPKzc3Vgw8+qPT0dPn4+Didg6IbFcZTG7DRSA0AAADwfJ06dZLdbi/1fEZGRrk/IyAgQG+++abefPPNG85B0Q0AqFBRVWqajgB4naDqv3xPWlS8839eYzoCnFSluukE8GYU3ShXQEDADT1izlpwAAAAADc7im6UKyUl5Ya+70bXggMAAACAt6DoNqCsmeObeXbYXRqv0UgNAAAAgKtQdBtQ1szxzTw77C6N12ikBgAAAMBVKLpRYX7uWvCbeZYf8GYBspqOACfdWsBYAa5U/YEI0xHgJNvp86YjwItRdKPC/Ny14DfzLD8AAAAA70TRDbdxo13SXY013QAAAABchaIbbuNGu6S7Gmu6AQAAAM+WkpKijIwMffXVV6pataratWunKVOmqGnTpg7X7du3T+PGjdOGDRtks9nUsmVLLV68WA0aNHBZFhZvAQAAAAC8yoYNG/Tcc89p69atWrNmja5evapu3brp0qVLhdccPHhQ7du3V7NmzbR+/Xp98cUXevnllxUQEODSLMx0A0VYW95tOgKcZM+7VP5FMC5Pq01HgJNOWe2mI8BJ4XeY32IT5Xt5QbDpCHDSxJjLpiPAxVauXOnwOi0tTWFhYdq+fbs6dOggSZowYYJ69eqlqVOnFl4XFRXl8izMdAMAAAAAPEJ+fr7Onz/v8JWfn1/u9507d06SFBISIkmy2Wxavny5mjRpou7duyssLEzR0dH64IMPXJ6ZmW6UKiEhQXl5N98n6SmPMdMNAAAAuKOUlBQlJSU5HJs4caISExNL/R673a74+Hi1b99erVq1knRtu+KLFy/q1VdfVXJysqZMmaKVK1eqb9++WrdunTp27OiyzBTdKFVeXp6mT59uOkaly/v0b6YjAAAAAChBQkKC4uPjHY75+/uX+T3PP/+8du/erc2bNxces9lskqRf//rXhTso3XnnndqyZYtmzpxJ0Q0AAAAAuPn4+/uXW2Rfb/jw4frnP/+pjRs36tZbby08HhoaqipVqqhFixYO1zdv3tyhOHcFim4Aniv3oukEcMKhq2dNR4CTAqqEmI4AJ/k9eKfpCHDC6CNfmI4AJ1WpH2Y6AlzMbrdr+PDhWrZsmdavX69GjRo5nPfz89M999yj/fv3Oxz/+uuvFRkZ6dIsFN0AAAAAAK/y3HPP6d1339U//vEPBQUFKTs7W5IUHBysqlWrSpLGjh2r/v37q0OHDoqJidHKlSuVmZmp9evXuzQLRbebCQgIKFxTcCOOHz9e7jXONkgr72d5a6M1GqkBAAAAnu2dd96RJHXq1MnheFpammJjYyVJffr00cyZM5WSkqIRI0aoadOmWrp0qdq3b+/SLBTdbiYlJeUXfb8zBbuzDdLK+1ne2miNRmoAAACAZ7Pb7U5dFxcXp7i4uArNQtENwGNZaoWbjgAndPVhnDzFr3Kvmo4AJ9kOfGs6AuBVbKfPm44AL2Y1HQAAAAAAAG9F0Q0AAAAAQAXh8XKUqrymbs40bbuepzReo5EaAAAAAFeh6Eapymvq9nO7rHtK4zUaqQEAAABwFYpuAB7Lfuyw6QhwwilLgekIcNJuf1/TEeCkX508ZToCnHDsuxqmI8BJwe0tpiPAi7GmGwAAAACACkLRDQAAAABABeHxcnikimzKRiM1AAAAwLMlJiYqKSnJ4Vh4eLiys7MlSbGxsZo/f77D+ejoaG3dutXlWSi6ccPK625e1M/tdl6WimzKRiM1AAAAwPO1bNlSH3/8ceFrHx8fh/M9evRQWlpa4Ws/P78KyUHRjRtWXnfzokaNGuWyGWpXFvDwXJaIRqYjwCn/MR0ATjpqvWo6ApzkExpkOgKccOZKxbyBR0W4bDoAKkCVKlVUt27dUs/7+/uXed5lOSr8NwDXcdUM9c/drgwAAACA58vPz1d+fr7DMX9/f/n7+xe79sCBA6pXr578/f0VHR2tyZMnKyoqqvD8+vXrFRYWppo1a6pjx46aNGmSwsLCXJ6Zohse6ec+2v5zsKYbAAAAcE8pKSnF1mpPnDhRiYmJDseio6O1YMECNWnSRD/++KOSk5PVrl07ffnll6pdu7Z69uypfv36KTIyUocPH9bLL7+szp07a/v27SUW8L8ERTc80s99tP3nYE03AAAA4J4SEhIUHx/vcKykIrlnz56F/27durXuu+8+3XbbbZo/f77i4+PVv3//wvOtWrXS3XffrcjISC1fvlx9+/Z1aWaKbgAAAACARyjtUfLyVKtWTa1bt9aBAwdKPB8REaHIyMhSz/8SFN2oNAEBATpy5IjpGPAi9mOHTUeAE/JkMx0BTvoVTZ88xrnNNBT1BHUDq5mOACflf3XedAQ4qfoNfl9+fr727dunBx54oMTzp06d0nfffaeIiIgbD1cKq8t/IlCKlJSUCmlMAAAAAADXGzNmjDZs2KDDhw/r3//+tx577DGdP39eQ4YM0cWLFzVmzBj961//0rfffqv169fr4YcfVmhoqPr06ePyLMx0w+25apsxZ9FIDQAAAPBs33//vQYMGKCTJ0+qTp06uvfee7V161ZFRkYqNzdXe/bs0YIFC3T27FlFREQoJiZG77//voKCXL8lI0W3l3Gmq7en7XHtqm3GnP59NFIDAAAAPNqiRYtKPVe1alWtWrWq0rJQdHsZZ7p6s8c1AAAAAFQOim5UqhvZX9vTZuYBODpjv2w6Apx0yodGaoAr1WtFcy5PUSXU13QEeDGKblSqG9lfm5l5AAAAAJ6Kohtu70Zmx38JGqkBAAAAcBWKbri9G5kd/yVopAYAAADAVSi6gSJsX35uOgKclZtrOgGcUNXCrcZTnLHYTEeAk/YeqmM6Apyw+yjrhD3FE7f8YDoCnBRsOsANsJoOAAAAAACAt6LoBgAAAACggvDMHypUQkKC8vLyTMf4WSY1N50AAAAAgLeg6EaFysvL0/Tp003H+FlyZrFFGQAAAODpjh49qnHjxumjjz5Sbm6umjRporlz5+quu+4qvGbfvn0aN26cNmzYIJvNppYtW2rx4sVq0KCBy3JQdAPwWPZTZ01HgBPqyc90BDipY26B6QhwUo7Fx3QEOKGbzznTEeCkgFD+//M2Z86c0f3336+YmBh99NFHCgsL08GDB1WzZs3Caw4ePKj27dvrmWeeUVJSkoKDg7Vv3z4FBAS4NAtFN0rlikfDjx8/7qI0AAAAAOCcKVOmqH79+kpLSys81rBhQ4drJkyYoF69emnq1KmFx6KiolyehaIbpXLFo+GjRvGoNgAAAADXyM/PV35+vsMxf39/+fv7Oxz75z//qe7du6tfv37asGGDbrnlFg0bNky/+93vJEk2m03Lly/Xiy++qO7du2vnzp1q1KiREhIS9Oijj7o0M0U3PEJlNmSjkRoAAADgnlJSUpSUlORwbOLEiUpMTHQ4dujQIb3zzjuKj4/XSy+9pG3btmnEiBHy9/fX4MGDdfz4cV28eFGvvvqqkpOTNWXKFK1cuVJ9+/bVunXr1LFjR5dlpuiGR6jMhmw0UgMAAADcU0JCguLj4x2OFZ3llq7NZN99992aPHmyJKlt27b68ssv9c4772jw4MGy2WySpF//+teFT+feeeed2rJli2bOnEnRDc8REBDgkkfMWRsOeK6D9hzTEeCkW/2qm44AJ9W6ajcdAU7Iv0LDO8DVSnqUvCQRERFq0aKFw7HmzZtr6dKlkqTQ0FBVqVKlxGs2b97susCi6EYFS0lJccnPYW04AAAAAGfdf//92r9/v8Oxr7/+WpGRkZIkPz8/3XPPPWVe4yoU3fAIrpoxdwZrugEAAADPNmrUKLVr106TJ0/W448/rm3btmnWrFmaNWtW4TVjx45V//791aFDB8XExGjlypXKzMzU+vXrXZqFohsewVUz5s5gTTcAAADg2e655x4tW7ZMCQkJ+t///V81atRIqampGjhwYOE1ffr00cyZM5WSkqIRI0aoadOmWrp0qdq3b+/SLBTdNyFnZ41ZRw0AAADAU/Xu3Vu9e/cu85q4uDjFxcVVaA6K7puQs7PGN+s6amvLu01HgJPsIYdNR4ATqlp2mY4AJ33tc9V0BDhp9K18MO4J9h6qYzoCnLWzlukEcFJt0wFugNV0AAAAAAAAvBUz3XC5hIQE5eXlmY5xw1IeY6YbAAAAgGtQdMPl8vLyNH36dNMxbljep38zHQEAAACAl+DxcgAAAAAAKggz3QA8V84l0wnghGUnd5mOACf1qN3KdAQ46fPDdU1HgDMspgPAWS3qnzcdAV6MohulcnZrsaLYagwAAAAArqHoRqmc3VqsKFdsNWayGRuN1AAAAAC4CkU33JLJZmw0UgMAAAC8S0pKil566SWNHDlSqampkiS73a6kpCTNmjVLZ86cUXR0tP785z+rZcuWLv3dFN1wuRt9LP16PKIOeI+G1cNNR4CTqlp4W+ApoqpeMB0BTsi/4mM6Apx08Yy/6QioQJ999plmzZqlNm3aOByfOnWqpk2bpvT0dDVp0kTJycnq2rWr9u/fr6CgIJf9fu6ucLkbfSz9eq54RB0AAADAze3ixYsaOHCgZs+ereTk5MLjdrtdqampmjBhgvr27StJmj9/vsLDw/Xuu+/q97//vcsysGUYAAAAAMAj5Ofn6/z58w5f+fn5pV7/3HPP6aGHHlKXLl0cjh8+fFjZ2dnq1q1b4TF/f3917NhRW7ZscWlmZrrhllzxiPqNopEaAAAA4J5SUlKUlJTkcGzixIlKTEwsdu2iRYu0fft2ff7558XOZWdnS5LCwx2XwYWHhysrK8t1gUXRDTflikfUbxSN1AAAAAD3lJCQoPj4eIdj/v7F1+R/9913GjlypFavXq2AgIBSf57FYnF4bbfbix37pSx2u93u0p8IwK3k5+crJSVFCQkJJf6HBPfBWHkOxsozME6eg7HyHIyVZ2CcpA8++EB9+vSRj8//b2hYUFAgi8Uiq9Wq/fv3q3HjxtqxY4fatm1beM2vf/1r1axZU/Pnz3dZFopuwMudP39ewcHBOnfunGrUqGE6DsrAWHkOxsozME6eg7HyHIyVZ2CcpAsXLhR7TPzpp59Ws2bNNG7cOLVs2VL16tXTqFGj9OKLL0qSLl++rLCwME2ZMsWljdR4vBwAAAAA4FWCgoLUqlUrh2PVqlVT7dq1C4+/8MILmjx5sm6//Xbdfvvtmjx5sgIDA/Xkk0+6NAtFNwAAAADgpvPiiy8qNzdXw4YN05kzZxQdHa3Vq1e7dI9uiaIbAAAAAHATWL9+vcNri8WixMTEEjufuxL7dANezt/fXxMnTrxpm2h4EsbKczBWnoFx8hyMledgrDwD4+ReaKQGAAAAAEAFYaYbAAAAAIAKQtENAAAAAEAFoegGAAAAAKCCUHQDAAAAAFBBKLoBAAAAAKggFN0AAAAAAFSQKqYDAKhYeXl5ev/993Xp0iV17dpVt99+u+lIAAAAwE2DfboBLzJ27FhdvnxZb7zxhiTp8uXLio6O1pdffqnAwEBdvXpVa9as0X333Wc4KYr68ssvVVBQUPjax8dHLVu2NJgIJTl69Kg+/fRTHT9+XDabzeHciBEjDKVCUXa7XX//+9+1bt26EscqIyPDUDJcj3HyHKdOndIrr7xS6lidPn3aUDKUhHuV+2GmG/AiH330kSZPnlz4+m9/+5uysrJ04MABNWjQQHFxcUpOTtby5csNpoQkbdq0SfHx8frss88kSffee69ycnL00+egFotFq1atUpcuXUzGxHXS0tI0dOhQ+fn5qXbt2rJYLIXnLBYLb2TcyMiRIzVr1izFxMQoPDzcYazgPhgnzzFo0CAdPHhQzzzzDGPl5rhXuSdmugEvUqNGDe3YsUONGzeWJA0YMEBBQUGaNWuWJGnXrl3q1auXfvjhB5MxoWtjc9999xXe/IKCgrR8+XJFRkbKbrdrxowZysrK0tKlSw0nxU/q16+voUOHKiEhQVYrLVHcWUhIiP7617+qV69epqOgDIyT5wgKCtLmzZt1xx13mI6CcnCvck+MBOBFrFarrv8cbevWrbr33nsLX9esWVNnzpwxEQ1FfPbZZ/rVr37lcOzWW29VZGSkGjZsqKeeekr/+te/DKVDSXJycvTEE0/wJsYDBAcHKyoqynQMlINx8hzNmjVTbm6u6RhwAvcq98RoAF6kWbNmyszMlHRtjfCRI0cUExNTeD4rK0vh4eGm4uE6R48eVUREROHr+fPnq27duoWvQ0JCdOrUKRPRUIpnnnlGS5YsMR0DTkhMTFRSUhJFgptjnDzH22+/rQkTJmjDhg06deqUzp8/7/AF98G9yj3xeDngRZYuXaoBAwbogQce0Jdffql77rmnsAiXpHHjxunw4cNavHixwZSQpLCwMC1evFidOnUq8fz69evVr18/nThxonKDoVQFBQXq3bu3cnNz1bp1a/n6+jqcnzZtmqFkKConJ0d9+/bVp59+qoYNGxYbqx07dhhKhusxTp7jwIEDGjBggHbu3Olw3G63y2KxODQChVncq9wTjdQAL/Kb3/xGK1as0PLly9WtWzcNHz7c4XxgYKCGDRtmKB2uFx0drQULFpRadKenpys6OrpyQ6FMkydP1qpVq9S0aVNJKtacBu4jNjZW27dv16BBg2j65MYYJ88xcOBA+fn56d1332Ws3Bz3KvfETDcAGLBu3Tp16dJF8fHxGjt2rMLCwiRJx48f15QpU/TGG29o9erV6ty5s+Gk+EmtWrU0ffp0xcbGmo6CclSrVk2rVq1S+/btTUdBGRgnzxEYGKidO3cWFnJwX9yr3BNruoGbSEZGhtq0aWM6BiTFxMTozTff1IwZMxQREaFatWopJCREEREReuutt5SamkrB7Wb8/f11//33m44BJ9SvX181atQwHQPlYJw8x913363vvvvOdAw4gXuVe2KmG/Ays2fP1urVq+Xr66uRI0cqOjpaa9eu1ejRo7V//3499dRT+stf/mI6Jv7ru+++09///ncdOHBAknT77bfrscceU/369Q0nQ1EpKSk6duyYZsyYYToKyrF8+XK9+eabmjlzpho2bGg6DkrBOHmOJUuWKDExUWPHji1xnTAf6LsP7lXuiaIb8CKvv/66XnrpJbVp00b79u2TJE2YMEHTpk3T8OHD9dxzzyk0NNRwSsAz9enTR2vXrlXt2rXVsmXLYm86MzIyDCVDUbVq1VJOTo6uXr2qwMDAYmN1+vRpQ8lwPcbJc5S0/ZTFYqGRmhviXuWeaKQGeJG5c+dq5syZiouL0/r169W5c2etXbtW33zzjWrWrGk6Hq6zceNGp67r0KFDBSeBs2rWrKm+ffuajgEnpKammo4AJzBOnuPw4cOmI8BJ3KvcEzPdgBcJDAzUV199pQYNGki6tq5n48aNdMF2QyXNGvzkp+6iFotFV69eraxIKMPVq1f1t7/9Td27d3fYTx3u58qVK3r22Wf18ssvKyoqynQclIJx8hxXrlxR06ZN9eGHH6pFixam46AM3KvcF43UAC+Sl5engICAwtd+fn6qU6eOwUQozZkzZ0r8Onr0qMaOHSt/f381a9bMdEz8V5UqVfSHP/xB+fn5pqOgHL6+vlq2bJnpGCgH4+Q5fH19lZ+fz3ZTHoB7lfvi8XLAy8yZM0fVq1eXdO0Tz/T09GLruEeMGGEiGq4THBzs8Npms2nevHlKSkqS1WrVn//8Zw0ZMsRQOpQkOjpaO3fuVGRkpOkoKEefPn30wQcfKD4+3nQUlIFx8hzDhw/XlClTNGfOHFWpQvngzrhXuSceLwe8SMOGDcv9JNpisejQoUOVlAjOyMjI0EsvvaQTJ04oISFBw4cPl7+/v+lYKGLJkiUaP368Ro0apbvuukvVqlVzOE/3XvcxadIkvf7663rwwQdLHCs+eHQPjJPn6NOnjz755BNVr15drVu3LjZWNOdyH9yr3BNFNwAYsmHDBo0bN0579uzRyJEjNW7cuGIz4HAfdO/1HI0aNSr1HB88ug/GyXM8/fTTZZ5PS0urpCQoD/cq90TRDdxETp06pYULF+qFF14wHeWm16tXL33yySd6+umnlZiYSMMTD5CVlVXmeR7lAwCYxr3KPVF0A17Obrdr9erVmjt3rv7xj3+oRo0aOnHihOlYNz2r1aoqVaqoWrVqZS4JYJ9a4Jf56W0OTaDcG+PkGU6cOKH9+/fLYrGoSZMmNGsFnEQnBMBLffvtt5o3b57S09N19OhRDRw4UMuXL1dMTIzpaBCP4nmqgwcPKjU1Vfv27ZPFYlHz5s01cuRI3XbbbaajoYgFCxbotdde04EDByRJTZo00dixY/XUU08ZTobrMU6e4dKlSxo+fLgWLFggm80mSfLx8dHgwYP15ptvKjAw0HBCXI97lfuh6Aa8SH5+vjIyMjRnzhxt2bJFPXv21LRp0zRgwACNHz+e/TXdCJ3JPc+qVav0yCOP6M4779T9998vu92uLVu2qGXLlsrMzFTXrl1NR8R/TZs2TS+//LKef/75wrH69NNPNXToUJ08eVKjRo0yHRFinDxJfHy8NmzYoMzMTN1///2SpM2bN2vEiBEaPXq03nnnHcMJ8RPuVe6Jx8sBLxIaGqoWLVpo0KBB6tevn2rVqiXp2h6bX3zxBUU38Au0bdtW3bt316uvvupwfPz48Vq9erV27NhhKBmKatSokZKSkjR48GCH4/Pnz1diYqIOHz5sKBmuxzh5jtDQUP39739Xp06dHI6vW7dOjz/+OMvW3Aj3KvfETDfgRQoKCmSxWGSxWOTj42M6DspQq1Ytp9Yusqbbfezbt0+LFy8udjwuLk6pqamVHwilOnbsmNq1a1fseLt27XTs2DEDiVASxslz5OTkKDw8vNjxsLAw5eTkGEiE0nCvck8U3YAXOXbsmJYuXaq5c+dq5MiR6tmzpwYNGkRjGjfEjc/z1KlTR7t27dLtt9/ucHzXrl0KCwszlAolady4sRYvXqyXXnrJ4fj7779fbPxgDuPkOe677z5NnDhRCxYsUEBAgCQpNzdXSUlJuu+++wynw/W4V7knim7AiwQEBGjgwIEaOHCgDh48qLS0NI0YMUJXr17VpEmTFBsbq86dOzML7gYaNWqkdu3aqUoV/hv2FL/73e/07LPP6tChQ2rXrp0sFos2b96sKVOmaPTo0abj4TpJSUnq37+/Nm7cqPvvv79wrD755JMSZ4BgBuPkOd544w316NFDt956q+644w5ZLBbt2rVLAQEBWrVqlel4uA73KvfEmm7AiyxYsED9+/eXv79/4TGbzaZVq1Zp7ty5yszMVFBQkE6ePGkwJaRrXV+PHTvGp84exG63KzU1VX/605/0ww8/SJLq1aunsWPHasSIETxR4ma2b9+u6dOna9++fbLb7WrRooVGjx6ttm3bmo6G6zBOniM3N1d//etf9dVXXxWO1cCBA1W1alXT0XAd7lXuiaIb8CLlFXInTpzQwoULFR8fX8nJUJTValV2djZFt4e6cOGCJCkoKMhwEgAASsa9yn1QdANehELOc1itVv3444+qU6eO6SiAV7LZbPrmm290/Pjxwn2Ff9KhQwdDqVAU4+Q5vv76a61fv77EsXrllVcMpQI8A0U34EUo5DyH1WrVs88+q8DAwDKvmzZtWiUlQnl+/PFHjRkzRp988omOHz+uorfPgoICQ8lQ1NatW/Xkk08qKyur2DhZLBbGyk0wTp5j9uzZ+sMf/qDQ0FDVrVvX4RFli8XCNlRuhHuVe6KDD+BlYmNjHdZ0lyQjI6OS0qAse/bskZ+fX6nnWXflXmJjY3XkyBG9/PLLioiIYHzc2NChQ3X33Xdr+fLljJUbY5w8R3JysiZNmqRx48aZjoJycK9yT8x0A17EarXq8ccfL7epSVpaWiUlQmlYCuB5goKCtGnTJt15552mo6Ac1apV0xdffKHGjRubjoIyME6eo0aNGtq1a5eioqJMR0E5uFe5J2a6AS8zY8YMCjkPwCfPnqd+/frFHtODe4qOjtY333xDMefmGCfP0a9fP61evVpDhw41HQXl4F7lnii6AS9CIec5yrshnjp1SgsXLtQLL7xQOYFQrtTUVI0fP15/+ctf1LBhQ9NxUIbhw4dr9OjRys7OVuvWreXr6+twvk2bNoaS4XqMk+do3LixXn75ZW3durXEsRoxYoShZCiKe5V74vFywIvwyLLnmD9/vp544gmH9fd2u12rV6/W3Llz9Y9//EM1atTQiRMnDKbE9WrVqqWcnBxdvXpVgYGBxd50nj592lAyFGW1Wosds1gsstvtNOhyI4yT52jUqFGp5ywWiw4dOlSJaVAW7lXuiZluwItMnjxZ//73v/Xwww8XHluwYIEmTpyoS5cu6dFHH9Wbb75ZbqM1VLwhQ4YU/vvbb7/VvHnzlJ6erqNHj2rgwIFavny5YmJiDCZEUampqaYjwEmHDx82HQFOYJw8B2PlObhXuSdmugEv0qNHD8XExBR2F92zZ4/+53/+R7GxsWrevLlee+01/f73v1diYqLZoFB+fr4yMjI0Z84cbdmyRT179tSTTz6pAQMG6IsvvlCLFi1MR8QNevXVVzV06FDVrFnTdBSU46GHHtKcOXMUERFhOgrKwDh5DhqueQ7uVZWLohvwIhEREcrMzNTdd98tSZowYYI2bNigzZs3S5KWLFmiiRMnau/evSZjQlJoaKhatGihQYMGqV+/fqpVq5YkydfXl6Lbw/Gm03MEBQXpiy++YKzcHOPkORgrz8G9qnIVX0wDwGOdOXNG4eHhha83bNigHj16FL6+55579N1335mIhiIKCgpksVhksVjk4+NjOg5ciM+yAQDujntV5aLoBrxIeHh44bqry5cva8eOHbrvvvsKz1+4cKFYQw2YcezYMT377LN67733VLduXf3mN7/RsmXL6EAPAADgZSi6AS/So0cPjR8/Xps2bVJCQoICAwP1wAMPFJ7fvXu3brvtNoMJ8ZOAgAANHDhQa9eu1Z49e9S8eXONGDFCV69e1aRJk7RmzRo69wIAAHgBim7AiyQnJ8vHx0cdO3bU7NmzNXv2bPn5+RWenzdvnrp162YwIUpy2223KTk5WVlZWfrwww+Vn5+v3r1702UeAOBReFoLKBlbhgFepE6dOtq0aZPOnTun6tWrF1srvGTJElWvXt1QOpTHarWqV69eatu2rerWratZs2aZjgQAgNNYJwyUjJluwAsFBweX2JwrJCTEYeYb5pw9e1YDBw5UnTp1VK9ePc2YMUM2m02vvPKKGjdurG3btmn+/PmmY0LX9rrPz893+voHHnhAVatWrcBEcJWXXnpJISEhpmOgHIyT5/joo490yy23mI4BJ3CvqlxsGQYABgwbNkyZmZnq37+/Vq5cqX379ql79+7Ky8vTxIkT1bFjR9MR8V8+Pj46duyYwsLCTEfBz7R3714dOXJEly9fdjj+yCOPGEoE6doHWSUJDg5W06ZN1axZs0pOhNLExcWVePynsRo0aBBP0Lkxu92udevWKTc3V+3atSvcnhSVj6IbAAyIjIzU3Llz1aVLFx06dEiNGzfWiBEjlJqaajoairBarcrOzqbo9iCHDh1Snz59tGfPHlkslsJHXn9ab0qTQrNKe+N/8eJF2Ww29erVS++++66CgoIqORmK6tOnT4nHz549qy+//FK+vr7atGkTez27gbNnz2rkyJHasWOH7r33Xv3pT39Sr169tGXLFknXliCuWbNGbdq0MZz05kTRDQAG+Pr6KisrS/Xq1ZMkBQYGatu2bWrVqpXhZCjKarXqxx9/VJ06dUxHgZMefvhh+fj4aPbs2YqKitK2bdt06tQpjR49Wq+//rrDrg5wHzabTdu3b9dvf/tbde3aVa+//rrpSChDbm6uBg8eLIvFosWLF5uOc9P77W9/q40bN2rw4MH68MMPZbVaZbfblZqaKqvVqhdffFHVq1dXZmam6ag3JYpuADDAx8dH2dnZhYVcUFCQdu/erUaNGhlOhqKsVqt69uxZbjf5jIyMSkqE8oSGhmrt2rVq06aNgoODtW3bNjVt2lRr167V6NGjtXPnTtMRUYaPP/5Yzz33nPbv3286Csrx+eefq2/fvjpy5IjpKDe9W265Re+++646duyoo0ePqn79+lq7dq06deokSdq2bZseeeQRZWdnmw16k6J7OQAYYLfbFRsbW1jI5eXlaejQoapWrZrDdRRy7iEoKIiGMx6koKCgcJ1paGiofvjhBzVt2lSRkZEUch6gcePG+v77703HgBNCQkJ09uxZ0zEg6ccff1STJk0kXSvAAwICVL9+/cLzDRo00IkTJ0zFu+lRdAOAAUOGDHF4PWjQIENJ4IwZM2awptuDtGrVSrt371ZUVJSio6M1depU+fn5adasWaw99QAHDx7UrbfeajoGnLBlyxbddtttpmNA15ZnXL9zjY+Pj8O+6eyhbhZFNwAYkJaWZjoCnOTMG5WjR4+yTY4b+eMf/6hLly5JkpKTk9W7d2898MADql27thYtWmQ4HUpjt9u1c+dOjR49Wg8//LDpOJC0e/fuEo+fO3dOn332mSZPnqzk5ORKToXSzJkzp/Apn6tXryo9PV2hoaGSpAsXLpiMdtNjTTcAAGUoq5Fadna2Jk2apDlz5ig3N9dAOjjr9OnTqlWrFrM9bqC0cbh48aIKCgrUo0cPvf/++2xF5QasVqvDDgDXq1OnjsaMGaOxY8caSIaiGjZs6NT/b4cPH66ENCiKmW4AAMqQkZGhF154QatXr5avr6/Gjx+v559/XomJiXr99dfVsmVLzZs3z3RMXCcuLk5vvPGGw5ZTISEhunTpkoYPH854GVba1og1atRQs2bN1Lx588oNhFKVVqAFBwerZs2alRsGZfr2229NR0AZmOkGAKAMw4YNU2Zmpvr376+VK1dq37596t69u/Ly8jRx4kR17NjRdEQU4ePjo2PHjhVbh3/y5EnVrVtXV69eNZQMkrRgwQL179+/3B0BAMBbUHQDAFCGyMhIzZ07V126dNGhQ4fUuHFjjRgxotTZOphz/vx52e121apVSwcOHHBYElBQUKDMzEyNHz9eP/zwg8GUKO1DEbi/vXv36siRI7p8+bLD8UceecRQIlzPZrMpPT1dGRkZ+vbbb2WxWNSoUSM99thjeuqpp1heYxCPlwMAUIYffvhBLVq0kCRFRUUpICBAv/3tbw2nQklq1qwpi8Uii8VSuHXO9SwWi5KSkgwkw/WY7/E8hw4dUp8+fbRnzx6HNd4/FXEFBQUm40HX/q4eeeQRrVixQnfccYdat24tu92uffv2KTY2VhkZGfrggw9Mx7xpUXQDAFAGm80mX1/fwtc+Pj7F9lOHe1i3bp3sdrs6d+6spUuXKiQkpPCcn5+fIiMjVa9ePYMJ8RNm3DzLyJEj1ahRI3388ceKiorStm3bdOrUKY0ePVqvv/666XiQlJ6ero0bN+qTTz5RTEyMw7m1a9fq0Ucf1YIFCzR48GBDCW9uPF4OAEAZrFarevbsWbj+NDMzU507dy5WeGdkZJiIhxJkZWWpQYMGFHZuqujfVGn4m3IfoaGhWrt2rdq0aaPg4GBt27ZNTZs21dq1azV69Gjt3LnTdMSbXrdu3dS5c2eNHz++xPOTJ0/Whg0btGrVqkpOBkmymg4AAIA7GzJkiMLCwhQcHKzg4GANGjRI9erVK3z90xfcR2RkpDZv3qxBgwapXbt2Onr0qCRp4cKF2rx5s+F0kKSgoKBif0P8TbmvgoKCwi3cQkNDC/siREZGav/+/Saj4b92796tHj16lHq+Z8+e+uKLLyoxEa7H4+UAAJQhLS3NdAT8TEuXLtVTTz2lgQMHaseOHcrPz5ckXbhwQZMnT9aKFSsMJ8SMGTNopOZBWrVqpd27dysqKkrR0dGaOnWq/Pz8NGvWLEVFRZmOB0mnT59WeHh4qefDw8N15syZSkyE6zHTDQAAvEpycrJmzpyp2bNnO6zHb9eunXbs2GEwGSTn1nP/9HQC3MMf//hH2Ww2Sdf+vrKysvTAAw9oxYoVeuONNwyng3TtaYQqVUqfT/Xx8WG7RIOY6QYAAF5l//796tChQ7HjNWrU0NmzZys/EBzY7fZSC+/s7GxNmjRJc+bMUW5ubiUnQ2m6d+9e+O+oqCjt3btXp0+fVq1ateid4CbsdrtiY2NL7ZXw0xM/MIOZbgAA4FUiIiL0zTffFDu+efNmHoV1AxkZGXrhhRdUp04d1atXTzNmzJDNZtMrr7yiqKgobd26VfPmzTMdE9eJi4vThQsXHI6FhIQoJydHcXFxhlLhekX7jxT9CgsLo3O5QXQvBwAAXmXq1KmaP3++5s2bp65du2rFihXKysrSqFGj9Morr+j55583HfGmNmzYMGVmZqp///5auXKl9u3bp+7duysvL08TJ05Ux44dTUdEET4+Pjp27FixdfgnT55U3bp1eWwZKAePlwMAAK/y4osv6ty5c4qJiVFeXp46dOggf39/jRkzhoLbDSxfvlxpaWnq0qWLhg0bpsaNG6tJkyZKTU01HQ1FnD9/Xna7XXa7XRcuXFBAQEDhuYKCAq1YsYKGeIATmOkGAABeKScnR3v37pXNZlOLFi0KtzyCWb6+vsrKylK9evUkSYGBgdq2bZtatWplOBmKslqtZa7ZtlgsSkpK0oQJEyoxFUri7GP+LN0wg5luAADgFXjT6RlsNptDV3kfHx9Vq1bNYCKUZt26dbLb7ercubOWLl2qkJCQwnN+fn6KjIws/PAEZqWnpysyMlJt27YVc6ruh5luAADgFaxWq1NvOpctW1aJqVCU1WpVz549C7ssZ2ZmqnPnzsUK74yMDBPxUIKsrCw1aNCATuVubNiwYVq0aJEaNGiguLg4DRo0yOFDEphF0Q0AALwCbzo9w9NPP+3UdWlpaRWcBD/Hpk2b9Je//EWHDh3SkiVLdMstt2jhwoVq1KiR2rdvbzoedG1bsIyMDM2bN09btmzRQw89pGeeeUbdunXjAxPDKLoBAIDX4E0n4HpLly7VU089pYEDB2rhwoXau3evoqKi9Pbbb+vDDz/UihUrTEdEEVlZWUpPT9eCBQt05coV7d27l74WBrFPNwAA8Br+/v4aMGCA1qxZo71796ply5YaNmyYIiMjdfHiRdPxAI+UnJysmTNnavbs2Q7r8du1a6cdO3YYTIbSWCwWWSwW2e122Ww203FuehTdAADAK/GmE3CN/fv3q0OHDsWO16hRQ2fPnq38QChRfn6+3nvvPXXt2lVNmzbVnj179NZbb+nIkSPMchtG0Q0AALwGbzoB14uIiNA333xT7PjmzZsVFRVlIBGKGjZsmCIiIjRlyhT17t1b33//vZYsWaJevXrJaqXkM4013QAAwCtc30jt6aef1qBBg1S7dm3TsQCPN3XqVM2fP1/z5s1T165dtWLFCmVlZWnUqFF65ZVX9Pzzz5uOeNOzWq1q0KCB2rZtW2b/CnYFMIOiGwAAeAXedAIVZ8KECZo+fbry8vIkXeufMGbMGP3f//2f4WSQpNjYWKeaRbIrgBkU3QAAwCvwphOoWDk5Odq7d69sNptatGjBkg3ASRTdAAAAAIqJi4tz6rp58+ZVcBKUp2/fvuVeY7FYtHTp0kpIg6KqmA4AAAAAwP2kp6crMjJSbdu2FfN07i04ONh0BJSBmW4AAAAAxVzfnDAuLk6DBg1SSEiI6ViAx6HoBgAAAFCi/Px8ZWRkaN68edqyZYseeughPfPMM+rWrZtTPRQAUHQDAAAAcEJWVpbS09O1YMECXblyRXv37qWZGuAEdkoHAAAAUC6LxSKLxSK73S6bzWY6DuAxKLoBAAAAlCg/P1/vvfeeunbtqqZNm2rPnj166623dOTIEWa5ASfRvRwAAABAMdc3Unv66ae1aNEi1a5d23QswOOwphsAAABAMVarVQ0aNFDbtm3LbJqWkZFRiakAz8NMNwAAAIBiBg8eTIdywAWY6QYAAAAAoILQSA0AAAAAgApC0Q0AAAAAQAWh6AYAAAAAoIJQdAMAAAAAUEEougEAAAAAqCAU3QAAAAAAVBCKbgAAAAAAKghFNwAAAAAAFeT/AZ5+ZsW4gyEtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(norm_scores);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 336,
   "id": "f37bd8eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.clustermap(norm_scores, col_cluster=False, cmap='magma');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "623e22fb",
   "metadata": {},
   "source": [
    "**TASK: Clearly Fandango is rating movies much higher than other sites, especially considering that it is then displaying a rounded up version of the rating. Let's examine the top 10 worst movies. Based off the Rotten Tomatoes Critic Ratings, what are the top 10 lowest rated movies? What are the normalized scores across all platforms for these movies? You may need to add the FILM column back in to your DataFrame of normalized scores to see the results.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 342,
   "id": "bd96133c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>RT_norm</th>\n",
       "      <th>RTU_norm</th>\n",
       "      <th>Meta_norm</th>\n",
       "      <th>MetaU_norm</th>\n",
       "      <th>IMDB_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm\n",
       "0      4.0     3.9      1.2       2.1        2.3         1.6        2.1\n",
       "1      4.5     4.5      3.6       4.0        3.0         3.5        3.6\n",
       "2      5.0     4.8      3.6       4.2        3.6         3.3        3.7\n",
       "3      5.0     4.8      4.0       4.2        3.4         3.4        3.7\n",
       "4      4.5     4.5      4.9       4.5        4.7         4.4        4.3\n",
       "..     ...     ...      ...       ...        ...         ...        ...\n",
       "140    3.5     3.5      4.4       3.2        3.4         3.2        3.4\n",
       "141    4.0     3.6      4.8       4.0        4.4         3.2        3.5\n",
       "142    4.5     4.2      4.6       4.2        3.4         3.5        3.9\n",
       "143    4.0     3.9      4.8       4.3        4.3         3.6        3.7\n",
       "144    3.5     3.1      3.0       2.3        3.4         2.9        3.2\n",
       "\n",
       "[145 rows x 7 columns]"
      ]
     },
     "execution_count": 342,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "id": "e7cfcc45",
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_scores = df[['STARS','RATING','RT_norm','RTU_norm','Meta_norm','MetaU_norm','IMDB_norm','FILM']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "id": "0af69038",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>RT_norm</th>\n",
       "      <th>RTU_norm</th>\n",
       "      <th>Meta_norm</th>\n",
       "      <th>MetaU_norm</th>\n",
       "      <th>IMDB_norm</th>\n",
       "      <th>FILM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>American Sniper (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>Inside Out (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>The Diary of a Teenage Girl (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.9</td>\n",
       "      <td>The Wrecking Crew (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.7</td>\n",
       "      <td>Tangerine (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Maps to the Stars (2015)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm  \\\n",
       "0      4.0     3.9      1.2       2.1        2.3         1.6        2.1   \n",
       "1      4.5     4.5      3.6       4.0        3.0         3.5        3.6   \n",
       "2      5.0     4.8      3.6       4.2        3.6         3.3        3.7   \n",
       "3      5.0     4.8      4.0       4.2        3.4         3.4        3.7   \n",
       "4      4.5     4.5      4.9       4.5        4.7         4.4        4.3   \n",
       "..     ...     ...      ...       ...        ...         ...        ...   \n",
       "140    3.5     3.5      4.4       3.2        3.4         3.2        3.4   \n",
       "141    4.0     3.6      4.8       4.0        4.4         3.2        3.5   \n",
       "142    4.5     4.2      4.6       4.2        3.4         3.5        3.9   \n",
       "143    4.0     3.9      4.8       4.3        4.3         3.6        3.7   \n",
       "144    3.5     3.1      3.0       2.3        3.4         2.9        3.2   \n",
       "\n",
       "                                   FILM  \n",
       "0           Fifty Shades of Grey (2015)  \n",
       "1                 Jurassic World (2015)  \n",
       "2                American Sniper (2015)  \n",
       "3                      Furious 7 (2015)  \n",
       "4                     Inside Out (2015)  \n",
       "..                                  ...  \n",
       "140  Kumiko, The Treasure Hunter (2015)  \n",
       "141  The Diary of a Teenage Girl (2015)  \n",
       "142            The Wrecking Crew (2015)  \n",
       "143                    Tangerine (2015)  \n",
       "144            Maps to the Stars (2015)  \n",
       "\n",
       "[145 rows x 8 columns]"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "id": "d62d433c",
   "metadata": {},
   "outputs": [
    {
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       "      <th>STARS</th>\n",
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       "      <td>1.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>Paul Blart: Mall Cop 2 (2015)</td>\n",
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       "      <th>25</th>\n",
       "      <td>4.5</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>1.4</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Fantastic Four (2015)</td>\n",
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       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>4.0</td>\n",
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       "      <td>1.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.4</td>\n",
       "      <td>Hot Pursuit (2015)</td>\n",
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       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>4.0</td>\n",
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       "      <td>1.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>The Boy Next Door (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Seventh Son (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Mortdecai (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Sinister 2 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>Unfinished Business (2015)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm  \\\n",
       "49    3.5     3.5      0.2       1.8        0.6         1.2        2.2   \n",
       "25    4.5     4.1      0.4       2.3        1.3         2.3        3.0   \n",
       "28    3.0     2.7      0.4       1.0        1.4         1.2        2.0   \n",
       "54    4.0     3.7      0.4       1.8        1.6         1.8        2.4   \n",
       "84    4.0     3.9      0.4       2.4        1.4         1.6        3.0   \n",
       "50    4.0     3.6      0.5       1.8        1.5         2.8        2.3   \n",
       "77    3.5     3.2      0.6       1.8        1.5         2.0        2.8   \n",
       "78    3.5     3.2      0.6       1.5        1.4         1.6        2.8   \n",
       "83    3.5     3.3      0.6       1.7        1.6         2.5        2.8   \n",
       "87    3.5     3.2      0.6       1.4        1.6         1.9        2.7   \n",
       "\n",
       "                             FILM  \n",
       "49  Paul Blart: Mall Cop 2 (2015)  \n",
       "25                 Taken 3 (2015)  \n",
       "28          Fantastic Four (2015)  \n",
       "54             Hot Pursuit (2015)  \n",
       "84        Hitman: Agent 47 (2015)  \n",
       "50       The Boy Next Door (2015)  \n",
       "77             Seventh Son (2015)  \n",
       "78               Mortdecai (2015)  \n",
       "83              Sinister 2 (2015)  \n",
       "87     Unfinished Business (2015)  "
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores.nsmallest(10, 'RT_norm')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb332d39",
   "metadata": {},
   "source": [
    "### **OR**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "id": "a014f18e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>STARS</th>\n",
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       "  <tbody>\n",
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       "      <th>49</th>\n",
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       "      <th>25</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.1</td>\n",
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       "      <th>84</th>\n",
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       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Hitman: Agent 47 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.4</td>\n",
       "      <td>Hot Pursuit (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2.3</td>\n",
       "      <td>The Boy Next Door (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>The Vatican Tapes (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.6</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>1.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>The Loft (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.2</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.9</td>\n",
       "      <td>2.7</td>\n",
       "      <td>Unfinished Business (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>Sinister 2 (2015)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm  \\\n",
       "49     3.5     3.5      0.2       1.8        0.6         1.2        2.2   \n",
       "25     4.5     4.1      0.4       2.3        1.3         2.3        3.0   \n",
       "28     3.0     2.7      0.4       1.0        1.4         1.2        2.0   \n",
       "84     4.0     3.9      0.4       2.4        1.4         1.6        3.0   \n",
       "54     4.0     3.7      0.4       1.8        1.6         1.8        2.4   \n",
       "50     4.0     3.6      0.5       1.8        1.5         2.8        2.3   \n",
       "109    3.0     2.9      0.6       1.0        1.8         2.7        2.3   \n",
       "88     4.0     3.6      0.6       2.0        1.2         1.2        3.2   \n",
       "87     3.5     3.2      0.6       1.4        1.6         1.9        2.7   \n",
       "83     3.5     3.3      0.6       1.7        1.6         2.5        2.8   \n",
       "\n",
       "                              FILM  \n",
       "49   Paul Blart: Mall Cop 2 (2015)  \n",
       "25                  Taken 3 (2015)  \n",
       "28           Fantastic Four (2015)  \n",
       "84         Hitman: Agent 47 (2015)  \n",
       "54              Hot Pursuit (2015)  \n",
       "50        The Boy Next Door (2015)  \n",
       "109       The Vatican Tapes (2015)  \n",
       "88                 The Loft (2015)  \n",
       "87      Unfinished Business (2015)  \n",
       "83               Sinister 2 (2015)  "
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores.sort_values('RT_norm', ascending = True).head(10)\n",
    "\n",
    "# norm_scores.sort_values('RT_norm', ascending = False).tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f00fcba0",
   "metadata": {},
   "source": [
    "**FINAL TASK: Visualize the distribution of ratings across all sites for the top 10 worst movies.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "id": "01b90486",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STARS</th>\n",
       "      <th>RATING</th>\n",
       "      <th>RT_norm</th>\n",
       "      <th>RTU_norm</th>\n",
       "      <th>Meta_norm</th>\n",
       "      <th>MetaU_norm</th>\n",
       "      <th>IMDB_norm</th>\n",
       "      <th>FILM</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>Fifty Shades of Grey (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.6</td>\n",
       "      <td>Jurassic World (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>3.7</td>\n",
       "      <td>American Sniper (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>Furious 7 (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.9</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>4.3</td>\n",
       "      <td>Inside Out (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>Kumiko, The Treasure Hunter (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>3.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>The Diary of a Teenage Girl (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>4.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3.9</td>\n",
       "      <td>The Wrecking Crew (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.9</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>4.3</td>\n",
       "      <td>3.6</td>\n",
       "      <td>3.7</td>\n",
       "      <td>Tangerine (2015)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>3.5</td>\n",
       "      <td>3.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>3.2</td>\n",
       "      <td>Maps to the Stars (2015)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>145 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     STARS  RATING  RT_norm  RTU_norm  Meta_norm  MetaU_norm  IMDB_norm  \\\n",
       "0      4.0     3.9      1.2       2.1        2.3         1.6        2.1   \n",
       "1      4.5     4.5      3.6       4.0        3.0         3.5        3.6   \n",
       "2      5.0     4.8      3.6       4.2        3.6         3.3        3.7   \n",
       "3      5.0     4.8      4.0       4.2        3.4         3.4        3.7   \n",
       "4      4.5     4.5      4.9       4.5        4.7         4.4        4.3   \n",
       "..     ...     ...      ...       ...        ...         ...        ...   \n",
       "140    3.5     3.5      4.4       3.2        3.4         3.2        3.4   \n",
       "141    4.0     3.6      4.8       4.0        4.4         3.2        3.5   \n",
       "142    4.5     4.2      4.6       4.2        3.4         3.5        3.9   \n",
       "143    4.0     3.9      4.8       4.3        4.3         3.6        3.7   \n",
       "144    3.5     3.1      3.0       2.3        3.4         2.9        3.2   \n",
       "\n",
       "                                   FILM  \n",
       "0           Fifty Shades of Grey (2015)  \n",
       "1                 Jurassic World (2015)  \n",
       "2                American Sniper (2015)  \n",
       "3                      Furious 7 (2015)  \n",
       "4                     Inside Out (2015)  \n",
       "..                                  ...  \n",
       "140  Kumiko, The Treasure Hunter (2015)  \n",
       "141  The Diary of a Teenage Girl (2015)  \n",
       "142            The Wrecking Crew (2015)  \n",
       "143                    Tangerine (2015)  \n",
       "144            Maps to the Stars (2015)  \n",
       "\n",
       "[145 rows x 8 columns]"
      ]
     },
     "execution_count": 355,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "0399348e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2400x1600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('\\n\\n\\n\\n\\n')\n",
    "# This signmifies some space before the plot or whatever comes next\n",
    "\n",
    "plt.figure(figsize=[12, 8], dpi=200)\n",
    "\n",
    "worst_films= norm_scores.nsmallest(10, 'RT_norm').drop('FILM', axis=1)\n",
    "sns.kdeplot(data= worst_films, shade=True, clip=[0, 5])\n",
    "\n",
    "plt.title(\"Ratings for RT Critics' Worst Reviewed Films\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3120b366",
   "metadata": {},
   "source": [
    "---\n",
    "----\n",
    "\n",
    "<img src=\"https://upload.wikimedia.org/wikipedia/en/6/6f/Taken_3_poster.jpg\">\n",
    "\n",
    "**Final thoughts: Wow! Fandango is showing around 3-4 star ratings for films that are clearly bad! Notice the biggest offender, [Taken 3!](https://www.youtube.com/watch?v=tJrfImRCHJ0). Fandango is displaying 4.5 stars on their site for a film with an [average rating of 1.86](https://en.wikipedia.org/wiki/Taken_3#Critical_response) across the other platforms!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "id": "a48d4700",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "STARS                    4.5\n",
       "RATING                   4.1\n",
       "RT_norm                  0.4\n",
       "RTU_norm                 2.3\n",
       "Meta_norm                1.3\n",
       "MetaU_norm               2.3\n",
       "IMDB_norm                3.0\n",
       "FILM          Taken 3 (2015)\n",
       "Name: 25, dtype: object"
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "norm_scores.iloc[25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92fee798",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}