GameDataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "05d33f32-bcd7-4f0f-bdd3-4ad69c4331e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Platform</th>\n",
       "      <th>Year</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Publisher</th>\n",
       "      <th>NA_Sales</th>\n",
       "      <th>EU_Sales</th>\n",
       "      <th>JP_Sales</th>\n",
       "      <th>Other_Sales</th>\n",
       "      <th>Global_Sales</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Wii Sports</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>41.49</td>\n",
       "      <td>29.02</td>\n",
       "      <td>3.77</td>\n",
       "      <td>8.46</td>\n",
       "      <td>82.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Super Mario Bros.</td>\n",
       "      <td>NES</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Platform</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>29.08</td>\n",
       "      <td>3.58</td>\n",
       "      <td>6.81</td>\n",
       "      <td>0.77</td>\n",
       "      <td>40.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Mario Kart Wii</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>Racing</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>15.85</td>\n",
       "      <td>12.88</td>\n",
       "      <td>3.79</td>\n",
       "      <td>3.31</td>\n",
       "      <td>35.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Wii Sports Resort</td>\n",
       "      <td>Wii</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>Sports</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>15.75</td>\n",
       "      <td>11.01</td>\n",
       "      <td>3.28</td>\n",
       "      <td>2.96</td>\n",
       "      <td>33.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Pokemon Red/Pokemon Blue</td>\n",
       "      <td>GB</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Role-Playing</td>\n",
       "      <td>Nintendo</td>\n",
       "      <td>11.27</td>\n",
       "      <td>8.89</td>\n",
       "      <td>10.22</td>\n",
       "      <td>1.00</td>\n",
       "      <td>31.37</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Rank                      Name Platform    Year         Genre Publisher   \n",
       "0     1                Wii Sports      Wii  2006.0        Sports  Nintendo  \\\n",
       "1     2         Super Mario Bros.      NES  1985.0      Platform  Nintendo   \n",
       "2     3            Mario Kart Wii      Wii  2008.0        Racing  Nintendo   \n",
       "3     4         Wii Sports Resort      Wii  2009.0        Sports  Nintendo   \n",
       "4     5  Pokemon Red/Pokemon Blue       GB  1996.0  Role-Playing  Nintendo   \n",
       "\n",
       "   NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  \n",
       "0     41.49     29.02      3.77         8.46         82.74  \n",
       "1     29.08      3.58      6.81         0.77         40.24  \n",
       "2     15.85     12.88      3.79         3.31         35.82  \n",
       "3     15.75     11.01      3.28         2.96         33.00  \n",
       "4     11.27      8.89     10.22         1.00         31.37  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Load the dataset\n",
    "df = pd.read_csv(r'C:\\Users\\mbugu\\OneDrive\\Desktop\\ML DATASET\\Video Game Sales\\vgsales.csv')\n",
    "\n",
    "# Display the first few rows\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "d8e918f7-5a05-4287-803c-7ed3e771bfb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   Rank                      Name Platform    Year         Genre Publisher   \n",
      "0     1                Wii Sports      Wii  2006.0        Sports  Nintendo  \\\n",
      "1     2         Super Mario Bros.      NES  1985.0      Platform  Nintendo   \n",
      "2     3            Mario Kart Wii      Wii  2008.0        Racing  Nintendo   \n",
      "3     4         Wii Sports Resort      Wii  2009.0        Sports  Nintendo   \n",
      "4     5  Pokemon Red/Pokemon Blue       GB  1996.0  Role-Playing  Nintendo   \n",
      "\n",
      "   NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  \n",
      "0     41.49     29.02      3.77         8.46         82.74  \n",
      "1     29.08      3.58      6.81         0.77         40.24  \n",
      "2     15.85     12.88      3.79         3.31         35.82  \n",
      "3     15.75     11.01      3.28         2.96         33.00  \n",
      "4     11.27      8.89     10.22         1.00         31.37  \n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 16598 entries, 0 to 16597\n",
      "Data columns (total 11 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Rank          16598 non-null  int64  \n",
      " 1   Name          16598 non-null  object \n",
      " 2   Platform      16598 non-null  object \n",
      " 3   Year          16327 non-null  float64\n",
      " 4   Genre         16598 non-null  object \n",
      " 5   Publisher     16540 non-null  object \n",
      " 6   NA_Sales      16598 non-null  float64\n",
      " 7   EU_Sales      16598 non-null  float64\n",
      " 8   JP_Sales      16598 non-null  float64\n",
      " 9   Other_Sales   16598 non-null  float64\n",
      " 10  Global_Sales  16598 non-null  float64\n",
      "dtypes: float64(6), int64(1), object(4)\n",
      "memory usage: 1.4+ MB\n",
      "None\n",
      "               Rank          Year      NA_Sales      EU_Sales      JP_Sales   \n",
      "count  16598.000000  16327.000000  16598.000000  16598.000000  16598.000000  \\\n",
      "mean    8300.605254   2006.406443      0.264667      0.146652      0.077782   \n",
      "std     4791.853933      5.828981      0.816683      0.505351      0.309291   \n",
      "min        1.000000   1980.000000      0.000000      0.000000      0.000000   \n",
      "25%     4151.250000   2003.000000      0.000000      0.000000      0.000000   \n",
      "50%     8300.500000   2007.000000      0.080000      0.020000      0.000000   \n",
      "75%    12449.750000   2010.000000      0.240000      0.110000      0.040000   \n",
      "max    16600.000000   2020.000000     41.490000     29.020000     10.220000   \n",
      "\n",
      "        Other_Sales  Global_Sales  \n",
      "count  16598.000000  16598.000000  \n",
      "mean       0.048063      0.537441  \n",
      "std        0.188588      1.555028  \n",
      "min        0.000000      0.010000  \n",
      "25%        0.000000      0.060000  \n",
      "50%        0.010000      0.170000  \n",
      "75%        0.040000      0.470000  \n",
      "max       10.570000     82.740000  \n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Load the dataset\n",
    "df = pd.read_csv(r'C:\\Users\\mbugu\\OneDrive\\Desktop\\ML DATASET\\Video Game Sales\\vgsales.csv')\n",
    "\n",
    "# Display the first few rows\n",
    "print(df.head())\n",
    "\n",
    "# Display basic information about the dataset\n",
    "print(df.info())\n",
    "\n",
    "# Display summary statistics\n",
    "print(df.describe())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "bfed30a6-9f00-4867-9678-2624d002851f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rank              0\n",
      "Name              0\n",
      "Platform          0\n",
      "Year            271\n",
      "Genre             0\n",
      "Publisher        58\n",
      "NA_Sales          0\n",
      "EU_Sales          0\n",
      "JP_Sales          0\n",
      "Other_Sales       0\n",
      "Global_Sales      0\n",
      "dtype: int64\n",
      "   Rank                      Name Platform    Year         Genre Publisher   \n",
      "0     1                Wii Sports      Wii  2006.0        Sports  Nintendo  \\\n",
      "1     2         Super Mario Bros.      NES  1985.0      Platform  Nintendo   \n",
      "2     3            Mario Kart Wii      Wii  2008.0        Racing  Nintendo   \n",
      "3     4         Wii Sports Resort      Wii  2009.0        Sports  Nintendo   \n",
      "4     5  Pokemon Red/Pokemon Blue       GB  1996.0  Role-Playing  Nintendo   \n",
      "\n",
      "   NA_Sales  EU_Sales  JP_Sales  Other_Sales  Global_Sales  \n",
      "0     41.49     29.02      3.77         8.46         82.74  \n",
      "1     29.08      3.58      6.81         0.77         40.24  \n",
      "2     15.85     12.88      3.79         3.31         35.82  \n",
      "3     15.75     11.01      3.28         2.96         33.00  \n",
      "4     11.27      8.89     10.22         1.00         31.37  \n"
     ]
    }
   ],
   "source": [
    "# Check for missing values\n",
    "print(df.isnull().sum())\n",
    "\n",
    "# Drop rows with missing values in critical columns (e.g., 'Name', 'Year')\n",
    "df.dropna(subset=['Name', 'Year'], inplace=True)\n",
    "\n",
    "# Fill missing values in other columns with appropriate values (e.g., 0 for sales)\n",
    "df['Publisher'].fillna('Unknown', inplace=True)\n",
    "\n",
    "# Display the first few rows of the cleaned dataset\n",
    "print(df.head())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3cfcf35d-1b3f-4648-b3aa-839851bfa8c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\mbugu\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n",
      "C:\\Users\\mbugu\\anaconda3\\Lib\\site-packages\\seaborn\\_oldcore.py:1119: FutureWarning: use_inf_as_na option is deprecated and will be removed in a future version. Convert inf values to NaN before operating instead.\n",
      "  with pd.option_context('mode.use_inf_as_na', True):\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "# Aggregate global sales by year\n",
    "sales_by_year = df.groupby('Year')['Global_Sales'].sum().reset_index()\n",
    "\n",
    "# Plot global sales trends over the years\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.lineplot(data=sales_by_year, x='Year', y='Global_Sales', marker='o')\n",
    "plt.title('Global Video Game Sales Over the Years')\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Global Sales (in millions)')\n",
    "plt.grid(True)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9f531569-a033-459c-b770-cffeecd174fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the top 10 selling games\n",
    "top_games = df.nlargest(10, 'Global_Sales')\n",
    "\n",
    "# Plot top-selling games\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data=top_games, x='Global_Sales', y='Name', palette='viridis')\n",
    "plt.title('Top 10 Selling Video Games')\n",
    "plt.xlabel('Global Sales (in millions)')\n",
    "plt.ylabel('Game')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "007090bf-797b-4628-9345-eb568c7110e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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37lxNnz5dZrNZHTp0UFxcnNMn49LVteLTp0/XsGHDtG/fPpUpU0ajR4/WhAkTHG1atWqlefPmadKkSfrPf/6jSpUqqV+/fipfvrz69OmT6zGGhYXphRde0FdffaVVq1bp999/l6enp6pXr65XX31VL7zwgmPjtieeeEK//fabZs2apXnz5ikkJESjRo3SqVOnnGLMjo+PjzZt2qSJEyfqvffecxyvVqVKFbVp08aRvDZu3Fg7d+7UyJEj9fvvv6tUqVJq0KCBvvrqK9WuXfsfx9O5c2fVrl1bY8aM0S+//KLQ0FAtWrRI3bt3z9K2UqVKatGihfbu3auePXvm+m+XWy+++KJSU1M1d+5cTZ48WbVq1dKsWbO0YsUKxyaD18ydO1fDhw9X586dZbPZ1Lt3by1YsOC6fffs2VM+Pj6Ki4tT9+7d5e7uriZNmig+Pt7xAw0AAP/EsP/1WzAAAIAi4rffflPVqlU1ePBgTZ482dXhAADgcszgAwCAIuXUqVM6fvy4Xn/9dbm5uWnIkCGuDgkAgEKBTfYAAECRMmfOHEVGRmr//v1atGiR07nvAAD8m/GJPgAAAAAAxQAz+AAAAAAAFAMk+AAAAAAAFAMk+AAAAAAAFAPsop8LmZmZOn36tPz8/GQYhqvDAQAAAAAUc3a7XRcvXlRgYKDc3G48R0+CnwunT59WUFCQq8MAAAAAAPzLJCYmqnLlyjdsQ4KfC35+fpKk5mXvk4ebp4ujKXirjy50dQgAAAAA8K9itVoVFBTkyEdvhAQ/F659lu/h5vmvTPD9/f1dHQIAAAAA/CvlZJm4yzfZi4uLU8OGDeXn56fy5cvr/vvv1+HDh7O0O3jwoDp37iyz2Sw/Pz81adJEv/zyi+O+zWbT4MGDVa5cOfn4+Khz5846deqUUx/nz5/X448/LrPZLLPZrMcff1wXLlzI7yECAAAAAJDvXJ7gf/311xo0aJC2bdumL774Qunp6WrXrp1SUlIcbY4dO6YWLVqoZs2aSkhI0J49e/TSSy/Jy8vL0ea5557TihUrtGTJEm3evFmXLl1Sp06dlJGR4WjTs2dP7d69W+vXr9f69eu1e/duPf744wU6XgAAAAAA8oNht9vtrg7ir37//XeVL19eX3/9tVq2bClJ6tGjhzw9PfXBBx9k+4zFYtFtt92mDz74QN27d5f0/xviffbZZ2rfvr0OHjyoWrVqadu2bWrcuLEkadu2bWratKkOHTqkGjVq/GNsVqtVZrNZEbfd/6/8RP/L5I9dHQIAAAAA/Ktcy0MtFss/Lpt2+Qz+31ksFklSmTJlJF09mm7dunUKDw9X+/btVb58eTVu3FgrV650PPP9998rLS1N7dq1c9QFBgbqjjvu0JYtWyRJW7duldlsdiT3ktSkSROZzWZHm7+z2WyyWq1OBQAAAACAwqhQJfh2u10vvPCCWrRooTvuuEOS9Ntvv+nSpUuaOHGiOnTooA0bNuiBBx7Qgw8+qK+//lqSlJycrBIlSqh06dJO/VWoUEHJycmONuXLl8/yzvLlyzva/F1cXJxjvb7ZbOaIPAAAAABAoVWodtF/5plntHfvXm3evNlRl5mZKUnq0qWLnn/+eUlS/fr1tWXLFs2aNUsRERHX7c9utzvtNJjdroN/b/NXMTExeuGFFxzX144nAAAAAACgsCk0M/iDBw/W6tWrFR8fr8qVKzvqy5UrJw8PD9WqVcup/e233+7YRT8gIEB//vmnzp8/79Tmt99+U4UKFRxtzpw5k+W9v//+u6PN35lMJvn7+zsVAAAAAAAKI5cn+Ha7Xc8884yWL1+ur776StWqVXO6X6JECTVs2DDL0XlHjhxR1apVJUl33323PD099cUXXzjuJyUl6ccff1SzZs0kSU2bNpXFYtH27dsdbb777jtZLBZHGwAAAAAAiiqXf6I/aNAgLV68WKtWrZKfn59jPbzZbJa3t7ckafjw4erevbtatmypqKgorV+/XmvWrFFCQoKjbZ8+fTR06FCVLVtWZcqU0bBhw1SnTh21adNG0tUZ/w4dOqhfv36aPXu2JOmpp55Sp06dcrSDPgAAAAAAhZnLj8m73vr3+fPnKzo62nE9b948xcXF6dSpU6pRo4YmTJigLl26OO5fuXJFw4cP1+LFi3X58mW1bt1aM2bMcFozf+7cOT377LNavXq1JKlz58569913VapUqRzFyjF5HJMHAAAAAAUpN8fkuTzBL0py84cFAAAAAOBW5SYPdfkafAAAAAAAcOtI8AEAAAAAKAZI8AEAAAAAKAZI8AEAAAAAKAYKZYI/c+ZM1a1bV/7+/vL391fTpk31v//9z3E/MjJShmHIMAyZTCZVqlRJ//nPf7R8+fJs+1u7dq0iIyPl5+enkiVLqmHDhlqwYEEBjQYAAAAAgPxXKBP8ypUra+LEidq5c6d27typVq1aqUuXLtq/f7+jTb9+/ZSUlKSjR49q2bJlqlWrlnr06KGnnnrKqa9p06apS5cuatasmb777jvt3btXPXr00IABAzRs2LCCHhoAAAAAAPmiyByTV6ZMGb3++uvq06ePIiMjVb9+fb399ttObebPn68nn3xSX3zxhdq0aaPExESFhoZq8ODBmjJlilPbadOm6dlnn9W2bdvUuHHjHMXAMXkAAAAAgIJUrI7Jy8jI0JIlS5SSkqKmTZvesG3v3r1VunRpx6f6n376qdLS0rKdqe/fv798fX310UcfXbc/m80mq9XqVAAAAAAAKIwKbYK/b98++fr6ymQyacCAAVqxYoVq1ap1w2fc3NwUHh6ukydPSpKOHDkis9msihUrZmlbokQJhYSE6MiRI9ftLy4uTmaz2VGCgoJuaUwAAAAAAOSXQpvg16hRQ7t379a2bdv09NNPq3fv3jpw4MA/Pme322UYRo7e8U9tY2JiZLFYHCUxMTHH8QMAAAAAUJAKbYJfokQJhYWFqUGDBoqLi1O9evX0zjvv3PCZjIwM/fTTT6pWrZokKTw8XBaLRadPn87S9s8//9Tx48dVvXr16/ZnMpkcO/lfKwAAAAAAFEaFNsH/O7vdLpvNdsM2Cxcu1Pnz59W1a1dJUteuXeXh4ZFlgz1JmjVrllJSUvTII4/kS7wAAAAAABQkD1cHkJ3Ro0fr3nvvVVBQkC5evKglS5YoISFB69evd7RJTU1VcnKy0tPT9euvv2r58uV666239PTTTysqKkqSVKVKFU2ePFnDhg2Tl5eXHn/8cXl6emrVqlUaPXq0hg4dmuMd9AEAAAAAKMwKZYJ/5swZPf7440pKSpLZbFbdunW1fv16tW3b1tHm/fff1/vvv68SJUqobNmyuvvuu7V06VI98MADTn09//zzCg0N1RtvvKF33nlHGRkZql27tmbOnKknnniioIcGAAAAAEC+MOx2u93VQRQVuTl/EAAAAACAW5WbPLTIrMEHAAAAAADXR4IPAAAAAEAxUCjX4Bd2XZsOlad7CVeHAdyUz/ZOd3UIAAAAAPIBM/gAAAAAABQDhTrBnzlzpurWrSt/f3/5+/uradOm+t///ue4HxkZKcMwZBiGTCaTKlWqpP/85z9avnx5lr7i4+MVFRWlMmXKqGTJkqpevbp69+6t9PT0ghwSAAAAAAD5olAn+JUrV9bEiRO1c+dO7dy5U61atVKXLl20f/9+R5t+/fopKSlJR48e1bJly1SrVi316NFDTz31lKPN/v37de+996phw4b65ptvtG/fPk2bNk2enp7KzMx0xdAAAAAAAMhThXoN/n/+8x+n69dee00zZ87Utm3bVLt2bUlSyZIlFRAQIEkKCgpSkyZNVLNmTT355JN6+OGH1aZNG33xxReqWLGiJk+e7OgrNDRUHTp0KLjBAAAAAACQjwr1DP5fZWRkaMmSJUpJSVHTpk1v2LZ3794qXbq041P9gIAAJSUl6ZtvvsnVO202m6xWq1MBAAAAAKAwKvQJ/r59++Tr6yuTyaQBAwZoxYoVqlWr1g2fcXNzU3h4uE6ePClJ6tatmx555BFFRESoYsWKeuCBB/Tuu+/+Y8IeFxcns9nsKEFBQXk1LAAAAAAA8lShT/Br1Kih3bt3a9u2bXr66afVu3dvHThw4B+fs9vtMgxDkuTu7q758+fr1KlTmjx5sgIDA/Xaa6+pdu3aSkpKum4fMTExslgsjpKYmJhn4wIAAAAAIC8V+gS/RIkSCgsLU4MGDRQXF6d69erpnXfeueEzGRkZ+umnn1StWjWn+kqVKunxxx/X9OnTdeDAAV25ckWzZs26bj8mk8mxg/+1AgAAAABAYVToE/y/s9vtstlsN2yzcOFCnT9/Xl27dr1um9KlS6tixYpKSUnJ6xABAAAAAChwhXoX/dGjR+vee+9VUFCQLl68qCVLlighIUHr1693tElNTVVycrLS09P166+/avny5Xrrrbf09NNPKyoqSpI0e/Zs7d69Ww888IBCQ0N15coV/fe//9X+/fs1bdo0Vw0PAAAAAIA8U6gT/DNnzujxxx9XUlKSzGaz6tatq/Xr16tt27aONu+//77ef/99lShRQmXLltXdd9+tpUuX6oEHHnC0adSokTZv3qwBAwbo9OnT8vX1Ve3atbVy5UpFRES4YmgAAAAAAOQpw263210dRFFhtVplNptlsVhYjw8AAAAAyHe5yUOL3Bp8AAAAAACQFQk+AAAAAADFQKFeg19YPdQqRp4ephy1XbftzXyOBgAAAAAAZvABAAAAACgWinyCHx0dLcMwZBiGPD09VaFCBbVt21bz5s1TZmamU9tdu3apW7duqlChgry8vBQeHq5+/frpyJEjLooeAAAAAIC8UeQTfEnq0KGDkpKSdPLkSf3vf/9TVFSUhgwZok6dOik9PV2StHbtWjVp0kQ2m02LFi3SwYMH9cEHH8hsNuull15y8QgAAAAAALg1xWINvslkUkBAgCSpUqVKuuuuu9SkSRO1bt1aCxYsUM+ePfXEE0+oY8eOWrFiheO5atWqqXHjxrpw4YKLIgcAAAAAIG8UiwQ/O61atVK9evW0fPlylS1bVn/88YdGjBiRbdtSpUplW2+z2WSz2RzXVqs1P0IFAAAAAOCWFYtP9K+nZs2aOnnypH766SfHdW7ExcXJbDY7SlBQUH6ECQAAAADALSvWCb7dbpdhGLLb7Tf1fExMjCwWi6MkJibmcYQAAAAAAOSNYp3gHzx4UNWqVVN4eLgk6dChQ7l63mQyyd/f36kAAAAAAFAYFdsE/6uvvtK+ffvUtWtXtWvXTuXKldPkyZOzbcsmewAAAACAoq5YbLJns9mUnJysjIwMnTlzRuvXr1dcXJw6deqkXr16yd3dXXPmzFG3bt3UuXNnPfvsswoLC9Mff/yhjz/+WL/88ouWLFni6mEAAAAAAHDTikWCv379elWsWFEeHh4qXbq06tWrp6lTp6p3795yc7v6kUKXLl20ZcsWxcXFqWfPnrJarQoKClKrVq306quvungEAAAAAADcGsN+szvQ/QtZrVaZzWZZLBbW4wMAAAAA8l1u8tBiuwYfAAAAAIB/ExJ8AAAAAACKgWKxBr+gdbtvvDw9TK4OAwAAoFBaGx/n6hAA4F+JGXwAAAAAAIqBYpHgR0dHyzAMGYYhT09PVahQQW3bttW8efOUmZnpaLdr1y516tRJ5cuXl5eXl4KDg9W9e3f98ccfLoweAAAAAIBbVywSfEnq0KGDkpKSdPLkSf3vf/9TVFSUhgwZok6dOik9PV2//fab2rRpo3Llyunzzz/XwYMHNW/ePFWsWFGpqamuDh8AAAAAgFtSbNbgm0wmBQQESJIqVaqku+66S02aNFHr1q21YMEClStXTlarVXPmzJGHx9VhV6tWTa1atXJl2AAAAAAA5IliM4OfnVatWqlevXpavny5AgIClJ6erhUrVshut+foeZvNJqvV6lQAAAAAACiMinWCL0k1a9bUyZMn1aRJE40ePVo9e/ZUuXLldO+99+r111/XmTNnrvtsXFyczGazowQFBRVg5AAAAAAA5FyxT/DtdrsMw5Akvfbaa0pOTtasWbNUq1YtzZo1SzVr1tS+ffuyfTYmJkYWi8VREhMTCzJ0AAAAAAByrNgn+AcPHlS1atUc12XLllW3bt00ZcoUHTx4UIGBgXrjjTeyfdZkMsnf39+pAAAAAABQGBXrBP+rr77Svn371LVr12zvlyhRQqGhoUpJSSngyAAAAAAAyFvFZhd9m82m5ORkZWRk6MyZM1q/fr3i4uLUqVMn9erVS2vXrtWSJUvUo0cPhYeHy263a82aNfrss880f/58V4cPAAAAAMAtKTYJ/vr161WxYkV5eHiodOnSqlevnqZOnarevXvLzc1NtWrVUsmSJTV06FAlJibKZDKpevXqmjNnjh5//HFXhw8AAAAAwC0x7Dk9Mw6yWq0ym82yWCysxwcAAAAA5Lvc5KHFeg0+AAAAAAD/FiT4AAAAAAAUA8VmDX5Beqjra/L0NLk6DCBPrfvsZVeHAAAAAOAWMIMPAAAAAEAxUCwS/OTkZA0ZMkRhYWHy8vJShQoV1KJFC82aNUupqamSpODgYBmGIcMw5O7ursDAQPXp00fnz593cfQAAAAAANy6Iv+J/vHjx9W8eXOVKlVKsbGxqlOnjtLT03XkyBHNmzdPgYGB6ty5syTp5ZdfVr9+/ZSRkaEjR47oqaee0rPPPqsPPvjAxaMAAAAAAODWFPkEf+DAgfLw8NDOnTvl4+PjqK9Tp466du2qv54C6Ofnp4CAAElSpUqV1KtXLy1ZsqTAYwYAAAAAIK8V6QT/7Nmz2rBhg2JjY52S+78yDCPb+l9//VVr165V48aNr9u/zWaTzWZzXFut1lsLGAAAAACAfFKk1+AfPXpUdrtdNWrUcKovV66cfH195evrq5EjRzrqR44cKV9fX3l7e6ty5coyDENvvvnmdfuPi4uT2Wx2lKCgoHwbCwAAAAAAt6JIJ/jX/H2Wfvv27dq9e7dq167tNAM/fPhw7d69W3v37tXGjRslSffdd58yMjKy7TcmJkYWi8VREhMT828QAAAAAADcgiL9iX5YWJgMw9ChQ4ec6kNCQiRJ3t7eTvXlypVTWFiYJKl69ep6++231bRpU8XHx6tNmzZZ+jeZTDKZOO8eAAAAAFD4FekZ/LJly6pt27Z69913lZKSkuvn3d3dJUmXL1/O69AAAAAAAChQRTrBl6QZM2YoPT1dDRo00NKlS3Xw4EEdPnxYH374oQ4dOuRI4iXp4sWLSk5OVlJSkrZv367hw4erXLlyatasmQtHAAAAAADArSvSn+hLUmhoqHbt2qXY2FjFxMTo1KlTMplMqlWrloYNG6aBAwc62o4dO1Zjx46VJN12221q2LChvvjiC5UtW9ZV4QMAAAAAkCcM+18PiscNWa1Wmc1mWSwW+fv7uzocAAAAAEAxl5s8tMh/og8AAAAAAEjwAQAAAAAoFor8GnxX6NozTh6eXq4OA/jX+t+Kca4OAQAAACh0mMEHAAAAAKAYKPQJfnJysoYMGaKwsDB5eXmpQoUKatGihWbNmqXU1FRJUnBwsAzDkGEYcnd3V2BgoPr06aPz589n22eNGjVUokQJ/frrrwU5FAAAAAAA8k2hTvCPHz+uO++8Uxs2bFBsbKx27dqlL7/8Us8//7zWrFmjL7/80tH25ZdfVlJSkn755RctWrRI33zzjZ599tksfW7evFlXrlxRt27dtGDBggIcDQAAAAAA+adQr8EfOHCgPDw8tHPnTvn4+Djq69Spo65du+qvJ/z5+fkpICBAklSpUiX16tVLS5YsydLn3Llz1bNnT0VERGjQoEEaPXq0DMPI/8EAAAAAAJCPCm2Cf/bsWcfM/V+T+7+6XmL+66+/au3atWrcuLFT/cWLF/XJJ5/ou+++U82aNZWSkqKEhARFRUVl24/NZpPNZnNcW63WmxwNAAAAAAD5q9B+on/06FHZ7XbVqFHDqb5cuXLy9fWVr6+vRo4c6agfOXKkfH195e3trcqVK8swDL355ptOzy5ZskTVq1dX7dq15e7urh49emju3LnXjSEuLk5ms9lRgoKC8naQAAAAAADkkUKb4F/z91n67du3a/fu3apdu7bT7Prw4cO1e/du7d27Vxs3bpQk3XfffcrIyHC0mTt3rh577DHH9WOPPably5frwoUL2b47JiZGFovFURITE/NwZAAAAAAA5J1Cm+CHhYXJMAwdOnTIqT4kJERhYWHy9vZ2qi9XrpzCwsJUvXp1tWrVSm+//ba2bNmi+Ph4SdKBAwf03XffacSIEfLw8JCHh4eaNGmiy5cv66OPPso2BpPJJH9/f6cCAAAAAEBhVGgT/LJly6pt27Z69913lZKSkuvn3d3dJUmXL1+WdHX2vmXLltqzZ492797tKCNGjLjhZ/oAAAAAABQFhTbBl6QZM2YoPT1dDRo00NKlS3Xw4EEdPnxYH374oQ4dOuRI4qWrG+glJycrKSlJ27dv1/Dhw1WuXDk1a9ZMaWlp+uCDD/TII4/ojjvucCp9+/bV999/rz179rhwpAAAAAAA3JpCneCHhoZq165datOmjWJiYlSvXj01aNBA06ZN07Bhw/TKK6842o4dO1YVK1ZUYGCgOnXqJB8fH33xxRcqW7asVq9erbNnz+qBBx7I8o7q1aurTp06zOIDAAAAAIo0w/7Xw+RxQ1arVWazWRaLhfX4AAAAAIB8l5s8tFDP4AMAAAAAgJwhwQcAAAAAoBjwcHUARdH90RPl4enl6jBQhGxYOtbVIQAAAAAo5pjBBwAAAACgGCgWCX5ycrKGDBmisLAweXl5qUKFCmrRooVmzZql1NRUR7tdu3apW7duqlChgry8vBQeHq5+/frpyJEjLoweAAAAAIBbV+QT/OPHj+vOO+/Uhg0bFBsbq127dunLL7/U888/rzVr1ujLL7+UJK1du1ZNmjSRzWbTokWLdPDgQX3wwQcym8166aWXXDwKAAAAAABuTZE/Jq9Dhw7av3+/Dh06JB8fnyz37Xa7Ll++rKpVq6pFixZasWJFljYXLlxQqVKlstTbbDbZbDbHtdVqVVBQkKIeiGENPnKFNfgAAAAAbsa/5pi8s2fPasOGDRo0aFC2yb0kGYahzz//XH/88YdGjBiRbZvskntJiouLk9lsdpSgoKC8Ch0AAAAAgDxVpBP8o0ePym63q0aNGk715cqVk6+vr3x9fTVy5Ej99NNPkqSaNWvmqv+YmBhZLBZHSUxMzLPYAQAAAADIS8XimDzDMJyut2/frszMTD366KOy2Wy62VUIJpNJJpMpL0IEAAAAACBfFekZ/LCwMBmGoUOHDjnVh4SEKCwsTN7e3pKk8PBwScrSDgAAAACA4qJIJ/hly5ZV27Zt9e677yolJeW67dq1a6dy5cpp8uTJ2d6/cOFCPkUIAAAAAEDBKNIJviTNmDFD6enpatCggZYuXaqDBw/q8OHD+vDDD3Xo0CG5u7vLx8dHc+bM0bp169S5c2d9+eWXOnnypHbu3KkRI0ZowIABrh4GAAAAAAC3pMgfkydJSUlJio2N1bp163Tq1CmZTCbVqlVL3bp108CBA1WyZElJ0s6dOxUXF6dNmzY5jrxr1aqVhg8frrCwsH98T26OJwAAAAAA4FblJg8tFgl+QSHBBwAAAAAUpNzkoUX+E30AAAAAAFBMjskraJ36TZJHCa886++rD17Ks74AAAAAAP9OzOADAAAAAFAMkOADAAAAAFAMFPoEPzk5WUOGDFFYWJi8vLxUoUIFtWjRQrNmzVJqaqokKTg4WIZhZCkTJ06UJJ08eVKGYah8+fK6ePGiU//169fX+PHjC3pYAAAAAADkqUK9Bv/48eNq3ry5SpUqpdjYWNWpU0fp6ek6cuSI5s2bp8DAQHXu3FmS9PLLL6tfv35Oz/v5+TldX7x4UW+88YYmTJhQYGMAAAAAAKAgFOoEf+DAgfLw8NDOnTvl4+PjqK9Tp466du2qv57w5+fnp4CAgBv2N3jwYL355psaNGiQypcv/4/vt9lsstlsjmur1XoTowAAAAAAIP8V2k/0z549qw0bNmjQoEFOyf1fGYaRqz4feeQRhYWF6eWXX85R+7i4OJnNZkcJCgrK1fsAAAAAACgohTbBP3r0qOx2u2rUqOFUX65cOfn6+srX11cjR4501I8cOdJRf60kJCQ4PXttXf57772nY8eO/WMMMTExslgsjpKYmJgnYwMAAAAAIK8V6k/0payz9Nu3b1dmZqYeffRRp8/nhw8frujoaKe2lSpVytJf+/bt1aJFC7300ktavHjxDd9tMplkMpluPngAAAAAAApIoU3ww8LCZBiGDh065FQfEhIiSfL29naqL1eunMLCwnLU98SJE9W0aVMNHz48b4IFAAAAAMDFCu0n+mXLllXbtm317rvvKiUlJU/7btSokR588EGNGjUqT/sFAAAAAMBVCu0MviTNmDFDzZs3V4MGDTR+/HjVrVtXbm5u2rFjhw4dOqS7777b0fbixYtKTk52er5kyZLy9/fPtu/XXntNtWvXlodHof4TAAAAAACQI4U6uw0NDdWuXbsUGxurmJgYnTp1SiaTSbVq1dKwYcM0cOBAR9uxY8dq7NixTs/3799fs2bNyrbv8PBwPfnkk3rvvfdyHdfa90de94cDAAAAAABcwbD/9TB53JDVapXZbJbFYiHBBwAAAADku9zkoYV2DT4AAAAAAMg5EnwAAAAAAIoBEnwAAAAAAIqBIp/gJycna8iQIQoLC5OXl5cqVKigFi1aaNasWUpNTXW027Vrl7p3766KFSvKZDKpatWq6tSpk9asWSO2IQAAAAAAFHWFehf9f3L8+HE1b95cpUqVUmxsrOrUqaP09HQdOXJE8+bNU2BgoDp37qxVq1bp4YcfVps2bbRw4UKFhobq7Nmz2rt3r8aMGaN77rlHpUqVcvVwAAAAAAC4aUV6F/0OHTpo//79OnTokHx8fLLct9vtSk1NVdWqVdWyZUstX748237sdrsMw/jH97GLPgAAAACgIOUmDy2yM/hnz57Vhg0bFBsbm21yL0mGYWjDhg06e/asRowYcd2+rpfc22w22Ww2x7XVar21oAEAAAAAyCdFdg3+0aNHZbfbVaNGDaf6cuXKydfXV76+vho5cqSOHDkiSU7tduzY4Wjj6+urtWvXZvuOuLg4mc1mRwkKCsq/AQEAAAAAcAuKbIJ/zd9n37dv367du3erdu3aTrPvf1W3bl3t3r1bu3fvVkpKitLT07NtFxMTI4vF4iiJiYl5Hj8AAAAAAHmhyH6iHxYWJsMwdOjQIaf6kJAQSZK3t7ckqXr16pKkw4cPq0mTJpIkk8mksLCwf3yHyWSSyWTKy7ABAAAAAMgXRXYGv2zZsmrbtq3effddpaSkXLddu3btVKZMGU2aNKkAowMAAAAAoGAV2QRfkmbMmKH09HQ1aNBAS5cu1cGDB3X48GF9+OGHOnTokNzd3eXr66s5c+Zo3bp1uu+++/T555/r+PHj2rt3ryZPnixJcnd3d/FIAAAAAAC4NUX6mDxJSkpKUmxsrNatW6dTp07JZDKpVq1a6tatmwYOHKiSJUtKknbu3KlJkybpm2++0blz52Q2m9WgQQM98cQTevjhhzkmDwAAAABQ6OQmDy3yCX5BIsEHAAAAABSk3OShRfoTfQAAAAAAcBUJPgAAAAAAxUCRPSbPldo9P0keJbxcHQb+JTbPfMnVIQAAAAAoApjBBwAAAACgGCj0CX50dLQMw9DEiROd6leuXOm0873dbtcbb7yh8PBwmUwmBQUFKTY2Nts+v/32W3l4eKh+/fr5GToAAAAAAAWm0Cf4kuTl5aVJkybp/Pnz120zZMgQzZkzR2+88YYOHTqkNWvWqFGjRlnaWSwW9erVS61bt87PkAEAAAAAKFBFYg1+mzZtdPToUcXFxWny5MlZ7h88eFAzZ87Ujz/+qBo1atywr/79+6tnz55yd3fXypUr8yliAAAAAAAKVpGYwXd3d1dsbKymTZumU6dOZbm/Zs0ahYSEaO3atapWrZqCg4PVt29fnTt3zqnd/PnzdezYMY0bNy5H77XZbLJarU4FAAAAAIDCqEgk+JL0wAMPqH79+tkm58ePH9fPP/+sTz75RP/973+1YMECff/993rooYccbX766SeNGjVKixYtkodHzj5ciIuLk9lsdpSgoKA8Gw8AAAAAAHmpyCT4kjRp0iQtXLhQBw4ccKrPzMyUzWbTf//7X91zzz2KjIzU3LlzFR8fr8OHDysjI0M9e/bUhAkTFB4enuP3xcTEyGKxOEpiYmJeDwkAAAAAgDxRJNbgX9OyZUu1b99eo0ePVnR0tKO+YsWK8vDwcEreb7/9dknSL7/8ogoVKmjnzp3atWuXnnnmGUlXfxSw2+3y8PDQhg0b1KpVqyzvM5lMMplM+TsoAAAAAADyQJFK8CVp4sSJql+/vlMy37x5c6Wnp+vYsWMKDQ2VJB05ckSSVLVqVfn7+2vfvn1O/cyYMUNfffWVPv30U1WrVq3gBgAAAAAAQD4ocgl+nTp19Oijj2ratGmOujZt2uiuu+7Sk08+qbfffluZmZkaNGiQ2rZt6/gh4I477nDqp3z58vLy8spSDwAAAABAUVSk1uBf88orr8hutzuu3dzctGbNGpUrV04tW7bUfffdp9tvv11LlixxYZQAAAAAABQcw/7XTBk3ZLVaZTabZbFY5O/v7+pwAAAAAADFXG7y0CI5gw8AAAAAAJyR4AMAAAAAUAwUuU32CoPWIybJo4SXq8MA8sTWqS+5OgQAAAAAeYAZfAAAAAAAioFCn+BHR0fLMAxNnDjRqX7lypUyDEOSlJCQIMMwsi3JycmSpJSUFI0cOVIhISHy8vLSbbfdpsjISK1du7bAxwQAAAAAQF4rEp/oe3l5adKkSerfv79Kly593XaHDx/Osqtg+fLlJUkDBgzQ9u3b9e6776pWrVo6e/astmzZorNnz+Zr7AAAAAAAFIQikeC3adNGR48eVVxcnCZPnnzdduXLl1epUqWyvbdmzRq988476tixoyQpODhYd999d36ECwAAAABAgSv0n+hLkru7u2JjYzVt2jSdOnXqpvoICAjQZ599posXL+b4GZvNJqvV6lQAAAAAACiMikSCL0kPPPCA6tevr3Hjxl23TeXKleXr6+soNWrUcNx77733tGXLFpUtW1YNGzbU888/r2+//faG74yLi5PZbHaUoKCgPBsPAAAAAAB5qcgk+JI0adIkLVy4UAcOHMj2/qZNm7R7925H+fzzzx33WrZsqePHj2vjxo3q2rWr9u/fr3vuuUevvPLKdd8XExMji8XiKImJiXk+JgAAAAAA8kKRSvBbtmyp9u3ba/To0dner1atmsLCwhwlODjY6b6np6fuuecejRo1Shs2bNDLL7+sV155RX/++We2/ZlMJvn7+zsVAAAAAAAKoyKxyd5fTZw4UfXr11d4ePgt91WrVi2lp6frypUrKlGiRB5EBwAAAACAaxS5BL9OnTp69NFHNW3atCz3fvvtN125csWprmzZsvL09FRkZKQeeeQRNWjQQGXLltWBAwc0evRoRUVFMTMPAAAAACjyitQn+te88sorstvtWepr1KihihUrOpXvv/9ektS+fXstXLhQ7dq10+23367Bgwerffv2+vjjjws6fAAAAAAA8pxhzy5TRrasVqvMZrMsFguz/gAAAACAfJebPLRIzuADAAAAAABnJPgAAAAAABQDJPgAAAAAABQDJPgAAAAAABQDRTrBj46OlmEYmjhxolP9ypUrZRiG49put+v9999X06ZN5e/vL19fX9WuXVtDhgzR0aNHCzpsAAAAAADyXJFO8CXJy8tLkyZN0vnz57O9b7fb1bNnTz377LPq2LGjNmzYoL1792rq1Kny9vbWq6++WsARAwAAAACQ9zxcHcCtatOmjY4ePaq4uDhNnjw5y/2lS5dqyZIlWrVqlTp37uyoDwkJUevWrcUpgQAAAACA4qDIz+C7u7srNjZW06ZN06lTp7Lc/+ijj1SjRg2n5P6v/vop/9/ZbDZZrVanAgAAAABAYVTkE3xJeuCBB1S/fn2NGzcuy70jR46oRo0aTnXPPfecfH195evrq8qVK1+337i4OJnNZkcJCgrK89gBAAAAAMgLxSLBl6RJkyZp4cKFOnDgQJZ7f5+lf/HFF7V7926NHTtWly5dum6fMTExslgsjpKYmJjncQMAAAAAkBeKTYLfsmVLtW/fXqNHj3aqr169ug4dOuRUd9tttyksLEzly5e/YZ8mk0n+/v5OBQAAAACAwqjYJPiSNHHiRK1Zs0Zbtmxx1D3yyCM6fPiwVq1a5cLIAAAAAADIX0V+F/2/qlOnjh599FFNmzbNUdejRw8tX75cPXr0UExMjNq3b68KFSro559/1tKlS+Xu7u7CiAEAAAAAyBvFagZfkl555RWno+8Mw9DSpUv19ttv67PPPlPr1q1Vo0YNPfnkkwoKCtLmzZtdGC0AAAAAAHnDsHMQfI5ZrVaZzWZZLBbW4wMAAAAA8l1u8tBiN4MPAAAAAMC/EQk+AAAAAADFQLHaZK+gRIyfKHeTl6vDAPLczrixrg4BAAAAwE1iBh8AAAAAgGKg2CT40dHRMgxDhmHI09NTISEhGjZsmFJSUhxtli1bpsjISJnNZvn6+qpu3bp6+eWXde7cORdGDgAAAADArSs2Cb4kdejQQUlJSTp+/LheffVVzZgxQ8OGDZMkvfjii+revbsaNmyo//3vf/rxxx81ZcoU7dmzRx988IGLIwcAAAAA4NYUqzX4JpNJAQEBkqSePXsqPj5eK1eu1BNPPKHY2Fi9/fbbGjJkiKN9cHCw2rZtqwsXLrgoYgAAAAAA8kaxSvD/ztvbW2lpaVq0aJF8fX01cODAbNuVKlUq23qbzSabzea4tlqt+REmAAAAAAC3rFh9ov9X27dv1+LFi9W6dWv99NNPCgkJkaenZ676iIuLk9lsdpSgoKB8ihYAAAAAgFtTrBL8tWvXytfXV15eXmratKlatmypadOmyW63yzCMXPcXExMji8XiKImJifkQNQAAAAAAt65YfaIfFRWlmTNnytPTU4GBgY4Z+/DwcG3evFlpaWm5msU3mUwymUz5FS4AAAAAAHmmWM3g+/j4KCwsTFWrVnVK5Hv27KlLly5pxowZ2T7HJnsAAAAAgKKuWM3gX0/jxo01YsQIDR06VL/++qseeOABBQYG6ujRo5o1a5ZatGjhtLs+AAAAAABFzU0l+FeuXNG0adMUHx+v3377TZmZmU73f/jhhzwJLi9NmjRJd999t6ZPn65Zs2YpMzNToaGheuihh9S7d29XhwcAAAAAwC0x7Ha7PbcP9ezZU1988YUeeughVahQIcsGduPGjcuzAAsTq9Uqs9ksi8Uif39/V4cDAAAAACjmcpOH3tQM/rp16/TZZ5+pefPmNxUgAAAAAADIWze1yV6lSpXk5+eX17EAAAAAAICbdFMJ/pQpUzRy5Ej9/PPPeR0PAAAAAAC4CTf1iX6DBg105coVhYSEqGTJklnOlj937lyeBAcAAAAAAHLmpmbwH3nkEf3666+KjY3VtGnT9NZbbzmV3IiOjpZhGDIMQ56engoJCdGwYcOUkpLiaLNs2TJFRkbKbDbL19dXdevW1csvv+z4IWHBggWOPv5a5syZI0kaMWKEgoODdfHiRad3/+c//1HLli2znAIAAAAAAEBRc1Mz+Fu2bNHWrVtVr169PAmiQ4cOmj9/vtLS0rRp0yb17dtXKSkpmjlzpl588UVNmjRJzz//vGJjYxUYGKiffvpJs2bN0gcffOA4v97f31+HDx926tdsNkuSXnnlFX322Wd64YUX9P7770uS5s2bp/j4eO3Zs0dubjf1OwcAAAAAAIXGTSX4NWvW1OXLl/MsCJPJpICAAElXj+CLj4/XypUr9cQTTyg2NlZvv/22I5GXpODgYLVt21YXLlxw1BmG4egju/4XLlyopk2bqmvXrqpVq5aef/55TZ48WaGhoXk2DgAAAAAAXOWmEvyJEydq6NCheu2111SnTp0sa/Bv9Yx4b29vpaWladGiRfL19dXAgQOzbVeqVKkc93n33XcrJiZGffv2VWhoqBo2bKinn376hs/YbDbZbDbHtdVqzfH7AAAAAAAoSDeV4Hfo0EGS1Lp1a6d6u90uwzCUkZFx0wFt375dixcvVuvWrfXTTz8pJCQkyw8I2bFYLPL19XVc+/r6Kjk52anNmDFjNH/+fH333Xc6cuSIDMO4YZ9xcXGaMGHCzQ0EAAAAAIACdFMJfnx8fJ4GsXbtWvn6+io9PV1paWnq0qWLpk2bpt69e/9jEn6Nn5+ffvjhB8d1duvqv/jiCyUlJcnNzU07duxQlSpVbthnTEyMXnjhBce11WpVUFBQDkcFAAAAAEDByXWCn5aWpvHjx2v27NkKDw/PkyCioqI0c+ZMeXp6KjAw0DFjHx4ers2bNystLe0fZ/Hd3NwUFhZ23fvnz59Xv379NHr0aHl6emrgwIGKiIhQuXLlrvuMyWSSyWS6uUEBAAAAAFCAcr19vKenp3788cccz6znhI+Pj8LCwlS1alWnRL5nz566dOmSZsyYke1zf91k758MHjxY5cuX15gxYzRq1CgFBQXpmWeeudXQAQAAAAAoFG7qfLhevXpp7ty5eR1LFo0bN9aIESM0dOhQjRgxQlu3btXPP/+sjRs3qlu3blq4cGGO+lmxYoU++eQTLVy4UJ6envLw8NCCBQu0YsUKLVu2LJ9HAQAAAABA/rupNfh//vmn5syZoy+++EINGjSQj4+P0/0333wzT4KTpEmTJunuu+/W9OnTNWvWLGVmZio0NFQPPfSQevfu/Y/P//HHHxowYIDGjRununXrOurvuOMOjRs3Lkef6gMAAAAAUNgZdrvdntuHoqKirt+hYeirr766paAKK6vVKrPZLIvFcstHAQIAAAAA8E9yk4cWil30AQAAAADArbmpNfh/derUKf366695EQsAAAAAALhJNzWDn5mZqVdffVVTpkzRpUuXJF09h37o0KF68cUXsz2DvjhpPjlO7l4cnwcAALLaPWa8q0MAAPxL3VSC/+KLL2ru3LmaOHGimjdvLrvdrm+//Vbjx4/XlStX9Nprr+V1nAAAAAAA4AZuaqp94cKFmjNnjp5++mnVrVtX9erV08CBA/X+++9rwYIFeRxizkVHR8swDBmGIU9PT4WEhGjYsGFKSUmRJC1btkyNGzeW2WyWn5+fateuraFDh7osXgAAAAAA8spNzeCfO3dONWvWzFJfs2ZNnTt37paDuhUdOnTQ/PnzlZaWpk2bNqlv375KSUlR165d1aNHD8XGxqpz584yDEMHDhzQxo0bXRovAAAAAAB54aYS/Hr16undd9/V1KlTnerfffdd1atXL08Cu1kmk0kBAQGSpJ49eyo+Pl4rV66UyWRSixYtNHz4cEfb8PBw3X///S6KFAAAAACAvHNTCf7kyZN133336csvv1TTpk1lGIa2bNmixMREffbZZ3kd4y3x9vZWWlqaAgICtHjxYv3444+64447cvSszWaTzWZzXFut1vwKEwAAAACAW3JTa/AjIiJ05MgRPfDAA7pw4YLOnTunBx98UIcPH9Y999yT1zHetO3bt2vx4sVq3bq1Bg8erIYNG6pOnToKDg5Wjx49NG/ePKcE/u/i4uJkNpsdJSgoqACjBwAAAAAg5wy73W7PScMHH3xQCxYskL+/v/773/+qe/fuMpkK11Fx0dHR+vDDD+Xl5aX09HSlpaWpS5cumjVrlsqXLy9JOnbsmOLj47Vt2zYtW7ZMVapU0datW1WyZMks/WU3gx8UFKQ7XhzFMXkAACBbHJMHAMhLVqtVZrNZFotF/v7+N2yb4wS/RIkS+vnnn1WxYkW5u7srKSnJkTQXFtHR0fr11181c+ZMeXp6KjAwUJ6entdtf+LECYWHh+u9997TE0888Y/9X/vDkuADAIDrIcEHAOSl3CT4OV6DX7NmTcXExCgqKkp2u10ff/zxdTvv1atX7iLOQz4+PgoLC8tR2+DgYJUsWdJxjB4AAAAAAEVVjhP8WbNm6YUXXtC6detkGIbGjBkjwzCytDMMw6UJ/vWMHz9eqamp6tixo6pWraoLFy5o6tSpSktLU9u2bV0dHgAAAAAAtyTHCX6zZs20bds2SZKbm5uOHDlS6D7Rv5GIiAhNnz5dvXr10pkzZ1S6dGndeeed2rBhg2rUqOHq8AAAAAAAuCU5XoP/Vz///LOqVKmS7Qz+L7/8oipVquRJcIVNbtY+AAAAAABwq3KTh97UMXkhISH6/fffs9SfPXtW1apVu5kuAQAAAADALbipBN9ut2c7e3/p0iV5eXndclAAAAAAACB3crwGX5JeeOEFSVc30nvppZeczo7PyMjQd999p/r16+dpgIVRs7fjOCYPAAAAAIqoPSPGuzqEfJGrBH/Xrl2Srs7g79u3TyVKlHDcK1GihOrVq6dhw4blbYQAAAAAAOAf5eoT/fj4eMXHx6t379763//+57iOj4/X559/rtmzZ6t69er5Emh0dLQMw5BhGPL09FRISIiGDRvmOMN+2bJlaty4scxms/z8/FS7dm0NHTrU8fzy5cvVtm1b3XbbbfL391fTpk31+eef50usAAAAAAAUtFzN4F8zf/78vI4jRzp06KD58+crLS1NmzZtUt++fZWSkqKuXbuqR48eio2NVefOnWUYhg4cOKCNGzc6nv3mm2/Utm1bxcbGqlSpUpo/f77+85//6LvvvtOdd97pkvEAAAAAAJBXbirBl6QdO3bok08+0S+//KI///zT6d7y5ctvObDsmEwmBQQESJJ69uyp+Ph4rVy5UiaTSS1atNDw4cMdbcPDw3X//fc7rt9++22nvmJjY7Vq1SqtWbOGBB8AAAAAUOTd1C76S5YsUfPmzXXgwAGtWLFCaWlpOnDggL766iuZzea8jvG6vL29lZaWpoCAAO3fv18//vhjjp/NzMzUxYsXVaZMmeu2sdlsslqtTgUAAAAAgMLophL82NhYvfXWW1q7dq1KlCihd955RwcPHtTDDz+sKlWq5HWM2dq+fbsWL16s1q1ba/DgwWrYsKHq1Kmj4OBg9ejRQ/PmzZPNZrvu81OmTFFKSooefvjh67aJi4uT2Wx2lKCgoPwYCgAAAAAAt+ymEvxjx47pvvvuk3T1s/mUlBQZhqHnn39e7733Xp4G+Fdr166Vr6+vvLy81LRpU7Vs2VLTpk2Tj4+P1q1bp6NHj2rMmDHy9fXV0KFD1ahRI6Wmpmbp56OPPtL48eO1dOlSlS9f/rrvi4mJkcVicZTExMR8GxsAAAAAALfiphL8MmXK6OLFi5KkSpUqOT6Nv3DhQrYJdV6JiorS7t27dfjwYV25ckXLly93StBDQ0PVt29fzZkzRz/88IMOHDigpUuXOvWxdOlS9enTRx9//LHatGlzw/eZTCb5+/s7FQAAAAAACqOb2mTvnnvu0RdffKE6dero4Ycf1pAhQ/TVV1/piy++UOvWrfM6RgcfHx+FhYXlqG1wcLBKlizpOEZPujpz/+STT+qjjz5yfIEAAAAAAEBxcFMJ/rvvvqsrV65IuvoZu6enpzZv3qwHH3xQL730Up4GmBPjx49XamqqOnbsqKpVq+rChQuaOnWq0tLS1LZtW0lXk/tevXrpnXfeUZMmTZScnCzp6kZ9BbkxIAAAAAAA+eGmP9EPDAy82oGbm0aMGKHVq1frzTffVOnSpfM0wJyIiIjQ8ePH1atXL9WsWVP33nuvkpOTtWHDBtWoUUOSNHv2bKWnp2vQoEGqWLGiowwZMqTA4wUAAAAAIK8ZdrvdnpOGuTkirriuVbdarTKbzbJYLMV2jAAAAACAwiM3eWiOP9EvVaqUDMO4YRu73S7DMJSRkZHTbgEAAAAAQB7IcYIfHx+fn3EAAAAAAIBbkOMEPyIiQqmpqRo+fLhWrlyptLQ0tWnTRlOnTlW5cuXyM8ZCp/mMWLl7mVwdBgAAAOCw+7kJrg4BgIvlapO9cePGacGCBbrvvvv0yCOP6IsvvtDTTz+dX7EBAAAAAIAcylWCv3z5cs2dO1fvvfee3nnnHa1bt04rV64skDX30dHRMgxDhmHI09NTISEhGjZsmOOc+2XLlqlx48Yym83y8/NT7dq1NXToUMfzmzdvVvPmzVW2bFl5e3urZs2aeuutt/I9bgAAAAAACkKOP9GXpMTERN1zzz2O60aNGsnDw0OnT59WUFBQngf3dx06dND8+fOVlpamTZs2qW/fvkpJSVHXrl3Vo0cPxcbGqnPnzjIMQwcOHNDGjRsdz/r4+OiZZ55R3bp15ePjo82bN6t///7y8fHRU089le+xAwAAAACQn3KV4GdkZKhEiRLOHXh4KD09PU+Duh6TyaSAgABJUs+ePRUfH6+VK1fKZDKpRYsWGj58uKNteHi47r//fsf1nXfeqTvvvNNxHRwcrOXLl2vTpk0k+AAAAACAIi9XCb7dbld0dLRMpv/fYO7KlSsaMGCAfHx8HHXLly/PuwhvwNvbW2lpaQoICNDixYv1448/6o477sjRs7t27dKWLVv06quvXreNzWaTzWZzXFut1luOGQAAAACA/JCrBL93795Z6h577LE8CyY3tm/frsWLF6t169YaPHiwNm3apDp16qhq1apq0qSJ2rVrp0cffdTpxwhJqly5sn7//Xelp6dr/Pjx6tu373XfERcXpwkT2I0UAAAAAFD4GXa73e7qIHIiOjpaH374oby8vJSenq60tDR16dJFs2bNUvny5SVJx44dU3x8vLZt26Zly5apSpUq2rp1q0qWLOno58SJE7p06ZK2bdumUaNG6d1339UjjzyS7Tuzm8EPCgrSHXEjOSYPAAAAhQrH5AHFk9VqldlslsVikb+//w3b5moG39WioqI0c+ZMeXp6KjAwUJ6enk73Q0NDFRoaqr59++rFF19UeHi4li5dqieeeMLRplq1apKkOnXq6MyZMxo/fvx1E3yTyZTlCwAAAAAAAAqjIpXg+/j4KCwsLEdtg4ODVbJkSccxetmx2+1OM/QAAAAAABRVRSrBv57x48crNTVVHTt2VNWqVXXhwgVNnTpVaWlpatu2rSRp+vTpqlKlimrWrClJ2rx5s9544w0NHjzYlaEDAAAAAJAnikWCHxERoenTp6tXr146c+aMSpcurTvvvFMbNmxQjRo1JEmZmZmKiYnRiRMn5OHhodDQUE2cOFH9+/fP9fu+HTj6H9c+AAAAAABQkIrMJnuFQW42NwAAAAAA4FblJg91K6CYAAAAAABAPioWn+gXtJZzXpW7N7vrA3/3/dOvuDoEAAAA4F+LGXwAAAAAAIoBEnwAAAAAAIqBIpPgR0dHyzAMGYYhT09PhYSEaNiwYY5z7pctW6bGjRvLbDbLz89PtWvX1tChQ7Pt69tvv5WHh4fq169fgCMAAAAAACD/FKk1+B06dND8+fOVlpamTZs2qW/fvkpJSVHXrl3Vo0cPxcbGqnPnzjIMQwcOHNDGjRuz9GGxWNSrVy+1bt1aZ86cccEoAAAAAADIe0UqwTeZTAoICJAk9ezZU/Hx8Vq5cqVMJpNatGih4cOHO9qGh4fr/vvvz9JH//791bNnT7m7u2vlypU3fJ/NZpPNZnNcW63WPBkHAAAAAAB5rch8op8db29vpaWlKSAgQPv379ePP/54w/bz58/XsWPHNG7cuBz1HxcXJ7PZ7ChBQUF5ETYAAAAAAHmuyCb427dv1+LFi9W6dWsNHjxYDRs2VJ06dRQcHKwePXpo3rx5TrPvP/30k0aNGqVFixbJwyNnHy7ExMTIYrE4SmJiYn4NBwAAAACAW1KkEvy1a9fK19dXXl5eatq0qVq2bKlp06bJx8dH69at09GjRzVmzBj5+vpq6NChatSokVJTU5WRkaGePXtqwoQJCg8Pz/H7TCaT/P39nQoAAAAAAIWRYbfb7a4OIieio6P166+/aubMmfL09FRgYKA8PT2v2/7EiRMKDw/Xe++9pwceeEClS5eWu7u7435mZqbsdrvc3d21YcMGtWrV6h9jsFqtMpvNqjdluNy9TXkyLqA4+f7pV1wdAgAAAFCsXMtDLRbLP046F6lN9nx8fBQWFpajtsHBwSpZsqRSUlLk7++vffv2Od2fMWOGvvrqK3366aeqVq1afoQLAAAAAECBKVIJ/vWMHz9eqamp6tixo6pWraoLFy5o6tSpSktLU9u2beXm5qY77rjD6Zny5cvLy8srSz0AAAAAAEVRsUjwIyIiNH36dPXq1UtnzpxR6dKldeedd2rDhg2qUaNGnr/vm75jWI8PAAAAAChUiswa/MIgN2sfAAAAAAC4VbnJQ4vULvoAAAAAACB7xeIT/YLW5sNX5MEu+sBN2/LEq64OAQAAACh2mMEHAAAAAKAYKDIJfnR0tAzDkGEY8vT0VEhIiIYNG6aUlBRJ0rJly9S4cWOZzWb5+fmpdu3aGjp0qOP5BQsWOJ43DEMVK1bUww8/rBMnTrhqSAAAAAAA5Jki9Yl+hw4dNH/+fKWlpWnTpk3q27evUlJS1LVrV/Xo0UOxsbHq3LmzDMPQgQMHtHHjRqfn/f39dfjwYdntdh06dEj9+/dX586dtXv3brm7u7toVAAAAAAA3LoileCbTCYFBARIknr27Kn4+HitXLlSJpNJLVq00PDhwx1tw8PDdf/99zs9bxiG4/mKFStq3Lhxeuyxx3T06NF8OU4PAAAAAICCUmQ+0c+Ot7e30tLSFBAQoP379+vHH3/M9fOSlJaWlu19m80mq9XqVAAAAAAAKIyKbIK/fft2LV68WK1bt9bgwYPVsGFD1alTR8HBwerRo4fmzZsnm8123edPnTql119/XZUrV1Z4eHi2beLi4mQ2mx0lKCgov4YDAAAAAMAtKVIJ/tq1a+Xr6ysvLy81bdpULVu21LRp0+Tj46N169bp6NGjGjNmjHx9fTV06FA1atRIqampjuctFot8fX3l4+OjoKAg/fnnn1q+fLlKlCiR7ftiYmJksVgcJTExsaCGCgAAAABArhSpNfhRUVGaOXOmPD09FRgYKE9PT6f7oaGhCg0NVd++ffXiiy8qPDxcS5cu1RNPPCFJ8vPz0w8//CA3NzdVqFBBPj4+N3yfyWSSycR59wAAAACAwq9IJfg+Pj4KCwvLUdvg4GCVLFnScYyeJLm5ueX4eQAAAAAAipIileBfz/jx45WamqqOHTuqatWqunDhgqZOnaq0tDS1bdvW1eEBAAAAAJDvitQa/OuJiIjQ8ePH1atXL9WsWVP33nuvkpOTtWHDBo6/AwAAAAD8Kxh2u93u6iCKCqvVKrPZLIvFIn9/f1eHAwAAAAAo5nKThxaLGXwAAAAAAP7tSPABAAAAACgGisUmewWt88cT5FGy6Byf92XPWFeHAAAAAADIZ8zgAwAAAABQDBSJBD86OlqGYcgwDHl6eiokJETDhg1znHG/bNkyNW7cWGazWX5+fqpdu7aGDh0qSZoyZYrMZrNSU1Oz9HvlyhWVKlVKb775ZoGOBwAAAACAvFYkEnxJ6tChg5KSknT8+HG9+uqrmjFjhoYNG6Yvv/xSPXr00EMPPaTt27fr+++/12uvvaY///xTktSrVy9dvnxZy5Yty9LnsmXLlJqaqscff7yghwMAAAAAQJ4qMmvwTSaTAgICJEk9e/ZUfHy8Vq5cKZPJpBYtWmj48OGOtuHh4br//vslSbfddpv+85//aN68eVkS+Xnz5qlz58667bbbCmwcAAAAAADkhyIzg/933t7eSktLU0BAgPbv368ff/zxum379Omjr7/+WidOnHDUnTx5UvHx8erTp891n7PZbLJarU4FAAAAAIDCqEgm+Nu3b9fixYvVunVrDR48WA0bNlSdOnUUHBysHj16aN68ebLZbI727du3V2BgoBYsWOComz9/vgIDA9WuXbvrvicuLk5ms9lRgoKC8nNYAAAAAADctCKT4K9du1a+vr7y8vJS06ZN1bJlS02bNk0+Pj5at26djh49qjFjxsjX11dDhw5Vo0aNHBvrubu7q3fv3lqwYIEyMzNlt9u1cOFCRUdHy93d/brvjImJkcVicZTExMSCGi4AAAAAALli2O12u6uD+CfR0dH69ddfNXPmTHl6eiowMFCenp7XbX/ixAmFh4frvffe0xNPPCFJOnbsmKpXr64NGzZIktq1a6effvpJoaGhOY7DarXKbDYr4v0X5FHSdGuDKkBf9ox1dQgAAAAAgJtwLQ+1WCzy9/e/Ydsis8mej4+PwsLCctQ2ODhYJUuWdByjJ0mhoaGKiIjQ/PnzZbfbFRkZmavkHgAAAACAwqzIJPjXM378eKWmpqpjx46qWrWqLly4oKlTpyotLU1t27Z1atunTx/169dPkjRnzhxXhAsAAAAAQL4oMmvwryciIkLHjx9Xr169VLNmTd17771KTk7Whg0bVKNGDae2Xbt2lclkkslk0oMPPuiiiAEAAAAAyHtFYg1+YZGbtQ8AAAAAANyq3OShRX4GHwAAAAAAkOADAAAAAFAsFPlN9lyhx+qx8szHY/JWPTgp3/oGAAAAABRPzOADAAAAAFAMFKkE/7ffflP//v1VpUoVmUwmBQQEqH379tq6datTuy1btsjd3V0dOnRw1EVHR8swjBsWAAAAAACKqiKV4Hft2lV79uzRwoULdeTIEa1evVqRkZE6d+6cU7t58+Zp8ODB2rx5s3755RdJ0jvvvKOkpCRHkaT58+dnqQMAAAAAoCgqMmvwL1y4oM2bNyshIUERERGSpKpVq6pRo0ZO7VJSUvTxxx9rx44dSk5O1oIFCzR27FiZzWaZzWantqVKlVJAQECBjQEAAAAAgPxSZGbwfX195evrq5UrV8pms1233dKlS1WjRg3VqFFDjz32mObPny+73X5T77TZbLJarU4FAAAAAIDCqMgk+B4eHlqwYIEWLlyoUqVKqXnz5ho9erT27t3r1G7u3Ll67LHHJEkdOnTQpUuXtHHjxpt6Z1xcnGPm32w2Kygo6JbHAQAAAABAfigyCb50dQ3+6dOntXr1arVv314JCQm66667tGDBAknS4cOHtX37dvXo0UPS1R8Funfvrnnz5t3U+2JiYmSxWBwlMTExr4YCAAAAAECeKjJr8K/x8vJS27Zt1bZtW40dO1Z9+/bVuHHjFB0drblz5yo9PV2VKlVytLfb7fL09NT58+dVunTpXL3LZDLJZMq/8+4BAAAAAMgrRWoGPzu1atVSSkqK0tPT9d///ldTpkzR7t27HWXPnj2qWrWqFi1a5OpQAQAAAADIN0VmBv/s2bPq1q2bnnzySdWtW1d+fn7auXOnJk+erC5dumjt2rU6f/68+vTpk2W3/Iceekhz587VM88846LoAQAAAADIX0Umwff19VXjxo311ltv6dixY0pLS1NQUJD69eun0aNH6+GHH1abNm2yJPfS1bX7sbGx+uGHH3TXXXe5IHoAAAAAAPKXYb/ZM+T+haxWq8xmsywWi/z9/V0dDgAAAACgmMtNHlrk1+ADAAAAAAASfAAAAAAAigUS/JvQ7/PRrg4BAAAAAAAnJPgAAAAAABQDhTrB/+2339S/f39VqVJFJpNJAQEBat++vbZu3epos2vXLnXr1k0VKlSQl5eXwsPD1a9fPx05ckSSdPLkSRmG4Sh+fn6qXbu2Bg0apJ9++slVQwMAAAAAIE8V6gS/a9eu2rNnjxYuXKgjR45o9erVioyM1Llz5yRJa9euVZMmTWSz2bRo0SIdPHhQH3zwgcxms1566SWnvr788kslJSVpz549io2N1cGDB1WvXj1t3LjRFUMDAAAAACBPFdpj8i5cuKDSpUsrISFBERERWe6npqaqatWqatGihVasWJHt86VKldLJkydVrVo17dq1S/Xr13fcz8zMVOvWrXXixAkdO3ZM7u7u/xjTteMJHv54kJZ2e/eWxgcAAAAAwD8pFsfk+fr6ytfXVytXrpTNZsty//PPP9cff/yhESNGZPt8qVKlbti/m5ubhgwZop9//lnff/99tm1sNpusVqtTAQAAAACgMCq0Cb6Hh4cWLFighQsXqlSpUmrevLlGjx6tvXv3SpJj/XzNmjVv+h3Xnj158mS29+Pi4mQ2mx0lKCjopt8FAAAAAEB+KrQJvnR1Df7p06e1evVqtW/fXgkJCbrrrru0YMEC5cXKgmt9GIaR7f2YmBhZLBZHSUxMvOV3AgAAAACQHwp1gi9JXl5eatu2rcaOHastW7YoOjpa48aNU3h4uCTp0KFDN933wYMHJUnVqlXL9r7JZJK/v79TAQAAAACgMCr0Cf7f1apVSykpKWrXrp3KlSunyZMnZ9vuwoULN+wnMzNTU6dOVbVq1XTnnXfmQ6QAAAAAABQcD1cHcD1nz55Vt27d9OSTT6pu3bry8/PTzp07NXnyZHXp0kU+Pj6aM2eOunXrps6dO+vZZ59VWFiY/vjjD3388cf65ZdftGTJEqf+kpOTlZqaqh9//FFvv/22tm/frnXr1uVoB30AAAAAAAqzQpvg+/r6qnHjxnrrrbd07NgxpaWlKSgoSP369dPo0aMlSV26dNGWLVsUFxennj17ymq1KigoSK1atdKrr77q1F+bNm0kSSVLllTVqlUVFRWl9957T2FhYQU+NgAAAAAA8pphz4vd6v4lcnP+IAAAAAAAtyo3eWiRW4MPAAAAAACyIsEHAAAAAKAYKLRr8Auz4QkjVMLH5OowUARNa/2Oq0MAAAAAUEwxgw8AAAAAQDHg8gT/t99+U//+/VWlShWZTCYFBASoffv22rp1qyQpODhYhmFo27ZtTs8999xzioyMdFyPHz9ehmFkKTVr1nS0OX78uB555BEFBgbKy8tLlStXVpcuXXTkyJECGSsAAAAAAPnF5Z/od+3aVWlpaVq4cKFCQkJ05swZbdy4UefOnXO08fLy0siRI/X111/fsK/atWvryy+/dKrz8Lg6xD///FNt27ZVzZo1tXz5clWsWFGnTp3SZ599JovFkvcDAwAAAACgALk0wb9w4YI2b96shIQERURESJKqVq2qRo0aObXr37+/Zs6cqc8++0wdO3a8bn8eHh4KCAjI9t6BAwd0/PhxffXVV6patarjXc2bN8+j0QAAAAAA4Dou/UTf19dXvr6+WrlypWw223XbBQcHa8CAAYqJiVFmZuZNveu2226Tm5ubPv30U2VkZOToGZvNJqvV6lQAAAAAACiMXJrge3h4aMGCBVq4cKFKlSql5s2ba/To0dq7d2+WtmPGjNGJEye0aNGi6/a3b98+x48G10rfvn0lSZUqVdLUqVM1duxYlS5dWq1atdIrr7yi48ePX7e/uLg4mc1mRwkKCrr1QQMAAAAAkA9cvsle165ddfr0aa1evVrt27dXQkKC7rrrLi1YsMCp3W233aZhw4Zp7Nix+vPPP7Ptq0aNGtq9e7dTee211xz3Bw0apOTkZH344Ydq2rSpPvnkE9WuXVtffPFFtv3FxMTIYrE4SmJiYp6NGwAAAACAvOTyBF+6uole27ZtNXbsWG3ZskXR0dEaN25clnYvvPCCLl++rBkzZmTbT4kSJRQWFuZUKlSo4NTGz89PnTt31muvvaY9e/bonnvu0auvvpptfyaTSf7+/k4FAAAAAIDCqFAk+H9Xq1YtpaSkZKn39fXVSy+9pNdeey1P1sNfO0Yvu3cBAAAAAFCUuDTBP3v2rFq1aqUPP/xQe/fu1YkTJ/TJJ59o8uTJ6tKlS7bPPPXUUzKbzfroo4+y3EtPT1dycrJTOXPmjCRp9+7d6tKliz799FMdOHBAR48e1dy5czVv3rzrvgsAAAAAgKLCpcfk+fr6qnHjxnrrrbd07NgxpaWlKSgoSP369dPo0aOzfcbT01OvvPKKevbsmeXe/v37VbFiRac6k8mkK1euqHLlygoODtaECRN08uRJGYbhuH7++efzZXwAAAAAABQUw263210dRFFhtVplNptlsVhYjw8AAAAAyHe5yUML5Rp8AAAAAACQOyT4AAAAAAAUAyT4AAAAAAAUAyT4AAAAAAAUAy5L8A3DuGGJjo52tI2Pj1enTp102223ycvLS6Ghoerevbu++eYbR5srV64oOjpaderUkYeHh+6///5s32uz2fTiiy+qatWqMplMCg0N1bx58/J5tAAAAAAA5C+XHZOXlJTk+OelS5dq7NixOnz4sKPO29tbkjRjxgw988wzevzxx7V06VJVq1ZNSUlJ2rFjh55//nl9//33kqSMjAx5e3vr2Wef1bJly6773ocfflhnzpzR3LlzFRYWpt9++03p6en5NEoAAAAAAApGoTgmb8GCBXruued04cIFp/pffvlFYWFheuaZZ/Tmm29mec5ut8swjCz10dHRunDhglauXOlUv379evXo0UPHjx9XmTJlch0nx+QBAAAAAApSsTkmb9myZUpLS9OIESOyvZ9dcn8jq1evVoMGDTR58mRVqlRJ4eHhGjZsmC5fvpxte5vNJqvV6lQAAAAAACiMCnWCf+TIEfn7+ysgIMBRt2zZMvn6+jrKvn37ctzf8ePHtXnzZv34449asWKF3n77bX366acaNGhQtu3j4uJkNpsdJSgo6JbHBAAAAABAfijUCb6UdZa+ffv22r17t9atW6eUlBRlZGTkuK/MzEwZhqFFixapUaNG6tixo958800tWLAg21n8mJgYWSwWR0lMTLzl8QAAAAAAkB9ctsleTlSvXl0Wi0XJycmOWXxfX1+FhYXJwyP3oVesWFGVKlWS2Wx21N1+++2y2+06deqUqlev7tTeZDLJZDLd2iAAAAAAACgAhXoG/6GHHpKnp6cmTZqUJ/01b95cp0+f1qVLlxx1R44ckZubmypXrpwn7wAAAAAAwBUKdYJfpUoVTZkyRe+884569+6t+Ph4nTx5Uj/88IOmTp0qSXJ3d3e0P3DggHbv3q1z587JYrFo9+7d2r17t+N+z549VbZsWT3xxBM6cOCAvvnmGw0fPlxPPvmk41g+AAAAAACKokL9ib4kDR48WLfffrvefPNNPfTQQ7JarSpbtqyaNm2q9evXq06dOo62HTt21M8//+y4vvPOOyVdPU5Puvp5/xdffKHBgwerQYMGKlu2rB5++GG9+uqrBTsoAAAAAADymGG/lv3iH+Xm/EEAAAAAAG5VbvLQQv2JPgAAAAAAyBkSfAAAAAAAigESfAAAAAAAigESfAAAAAAAioEimeDPmjVLfn5+Sk9Pd9RdunRJnp6euueee5zabtq0SYZh6MiRI9q1a5c6deqk8uXLy8vLS8HBwerevbv++OOPgh4CAAAAAAB5qkgm+FFRUbp06ZJ27tzpqNu0aZMCAgK0Y8cOpaamOuoTEhIUGBioUqVKqU2bNipXrpw+//xzHTx4UPPmzVPFihWd2gMAAAAAUBR5uDqAm1GjRg0FBgYqISFBTZo0kXQ1ke/SpYvi4+O1ZcsWtWnTxlEfFRWlLVu2yGq1as6cOfLwuDrsatWqqVWrVi4bBwAAAAAAeaVIzuBLUmRkpOLj4x3X8fHxioyMVEREhKP+zz//1NatWxUVFaWAgAClp6drxYoVstvtOXqHzWaT1Wp1KgAAAAAAFEZFOsH/9ttvlZ6erosXL2rXrl1q2bKlIiIilJCQIEnatm2bLl++rKioKDVp0kSjR49Wz549Va5cOd177716/fXXdebMmeu+Iy4uTmaz2VGCgoIKaHQAAAAAAOSOYc/pdHYhc/ToUVWvXl1btmzR+fPnNXz4cO3fv1/JycmqUqWKzp8/rylTpmju3Ln6+eefHc+dPXtWX331lbZt26aVK1fq3Llz+uabb1SnTp0s77DZbLLZbI5rq9WqoKAgWSwW+fv7F8g4AQAAAAD/XlarVWazOUd5aJGdwQ8LC1PlypUVHx+v+Ph4RURESJICAgJUrVo1ffvtt4qPj8+yxr5s2bLq1q2bpkyZooMHDyowMFBvvPFGtu8wmUzy9/d3KgAAAAAAFEZFNsGXru6mn5CQoISEBEVGRjrqIyIi9Pnnn2vbtm2Kioq67vMlSpRQaGioUlJSCiBaAAAAAADyT5HcRf+aqKgoDRo0SGlpaY4ZfOlqgv/000/rypUrjgR/7dq1WrJkiXr06KHw8HDZ7XatWbNGn332mebPn++qIQAAAAAAkCeKfIJ/+fJl1axZUxUqVHDUR0RE6OLFiwoNDXVsjFerVi2VLFlSQ4cOVWJiokwmk6pXr645c+bo8ccfd9UQAAAAAADIE0V2kz1XyM3mBgAAAAAA3Kp/xSZ7AAAAAADg/5HgAwAAAABQDBTpNfiu8v53j8rbx9PVYQAAAKAQG9hsuatDAPAv86+awU9ISJBhGLpw4YIkacGCBSpVqpRLYwIAAAAAIC8U2QR/1qxZ8vPzU3p6uqPu0qVL8vT01D333OPUdtOmTTIMQ4GBgUpKSpLZbJYkde/eXUeOHCnQuAEAAAAAyA9FNsGPiorSpUuXtHPnTkfdpk2bFBAQoB07dig1NdVRn5CQoMDAQIWHhysgIECGYUiSvL29Vb58+QKPHQAAAACAvFZkE/waNWooMDBQCQkJjrqEhAR16dJFoaGh2rJli1N9VFQUn+gDAAAAAIqtIpvgS1JkZKTi4+Md1/Hx8YqMjFRERISj/s8//9TWrVsVFRWV6/5tNpusVqtTAQAAAACgMCryCf63336r9PR0Xbx4Ubt27VLLli0VERHhmNnftm2bLl++fFMJflxcnMxms6MEBQXl8QgAAAAAAMgbRTrBj4qKUkpKinbs2KFNmzYpPDxc5cuXV0REhHbs2KGUlBQlJCSoSpUqCgkJyXX/MTExslgsjpKYmJgPowAAAAAA4NZ5uDqAWxEWFqbKlSsrPj5e58+fV0REhCQpICBA1apV07fffqv4+Hi1atXqpvo3mUwymUx5GTIAAAAAAPmiSM/gS3JsnpeQkKDIyEhHfUREhD7//HNt27btpj7PBwAAAACgKCkWCf7mzZu1e/duxwy+dDXBf//993XlyhUSfAAAAABAsVcsEvzLly8rLCxMFSpUcNRHRETo4sWLCg0NZXM8AAAAAECxZ9jtdrurgygqrFarzGazLBaL/P39XR0OAAAAAKCYy00eWuRn8AEAAAAAAAk+AAAAAADFQpE+Js9Vlu54QN4+xf9P91iTz10dAgAAAAAgh4rFDH5CQoIMw9CFCxckSQsWLFCpUqVcGhMAAAAAAAWp0CX4s2bNkp+fn9LT0x11ly5dkqenp+655x6ntps2bZJhGAoMDFRSUpLMZrMkqXv37jpy5Iij3fjx41W/fv0s77pw4YIMw1BCQkK+jAUAAAAAgIJS6BL8qKgoXbp0STt37nTUbdq0SQEBAdqxY4dSU1Md9QkJCQoMDFR4eLgCAgJkGIYkydvbW+XLly/w2AEAAAAAcJVCl+DXqFFDgYGBTrPqCQkJ6tKli0JDQ7Vlyxan+qioKD7RBwAAAAD86xW6BF+SIiMjFR8f77iOj49XZGSkIiIiHPV//vmntm7dqqioqHyLw2azyWq1OhUAAAAAAAqjQpvgf/vtt0pPT9fFixe1a9cutWzZUhEREY6Z/W3btuny5cv5muDHxcXJbDY7SlBQUL69CwAAAACAW1EoE/yoqCilpKRox44d2rRpk8LDw1W+fHlFRERox44dSklJUUJCgqpUqaKQkJB8iyMmJkYWi8VREhMT8+1dAAAAAADcikJ5mHtYWJgqV66s+Ph4nT9/XhEREZKkgIAAVatWTd9++63i4+PVqlWrHPXn7+8vi8WSpf7amv1ru+//nclkkslkurlBAAAAAABQgArlDL4kx+Z5CQkJioyMdNRHRETo888/17Zt23L8eX7NmjV16tQpJScnO9Xv2LFDbm5uCgsLy8vQAQAAAAAocIU6wd+8ebN2797tmMGXrib477//vq5cuZLjBL9du3a6/fbb1aNHD3377bc6ceKEVq1apWHDhmnAgAHy8/PLr2EAAAAAAFAgCuUn+tLVBP/y5cuqWbOmKlSo4KiPiIjQxYsXFRoamuNN7zw8PLRhwwaNHj1ajz76qH777TdVrVpVffv21YgRI/JrCAAAAAAAFBjDbrfbXR1EUWG1WmU2m2WxWOTv7+/qcAAAAAAAxVxu8tBC+4k+AAAAAADIORJ8AAAAAACKgUK7Br8w+9/Odirpw58OAAAAxcN/Gm92dQgA8gAz+AAAAAAAFAMuTfAzMjLUrFkzde3a1aneYrEoKChIY8aM0dmzZ9WhQwcFBgbKZDIpKChIzzzzjKxWq9Mzdrtdb7zxhsLDwx3tYmNjndp8/fXXuvvuu+Xl5aWQkBDNmjUr38cIAAAAAEBBcGmC7+7uroULF2r9+vVatGiRo37w4MEqU6aMxo4dKzc3N3Xp0kWrV6/WkSNHtGDBAn355ZcaMGCAU19DhgzRnDlz9MYbb+jQoUNas2aNGjVq5Lh/4sQJdezYUffcc4927dql0aNH69lnn9WyZcsKbLwAAAAAAOSXQnFM3tSpUzV+/Hj9+OOP2rFjh7p166bt27erfv36123/+uuvKzExUZJ08OBB1a1bVz/++KNq1KiR7TMjR47U6tWrdfDgQUfdgAEDtGfPHm3dujXbZ2w2m2w2m+PaarUqKChISzY2Zg0+AAAAig3W4AOFV5E7Jm/w4MGqV6+eevXqpaeeekpjx469bnJ/+vRpLV++XBEREY66NWvWKCQkRGvXrlW1atUUHBysvn376ty5c442W7duVbt27Zz6at++vXbu3Km0tLRs3xUXFyez2ewoQUFBtz5YAAAAAADyQaFI8A3D0MyZM7Vx40ZVqFBBo0aNytLmkUceUcmSJVWpUiX5+/trzpw5jnvHjx/Xzz//rE8++UT//e9/tWDBAn3//fd66KGHHG2Sk5NVoUIFpz4rVKig9PR0/fHHH9nGFRMTI4vF4ijXvhgAAAAAAKCwKRQJviTNmzdPJUuW1IkTJ3Tq1Kks99966y398MMPWrlypY4dO6YXXnjBcS8zM1M2m03//e9/dc899ygyMlJz585VfHy8Dh8+7GhnGIZTn9dWJ/y9/hqTySR/f3+nAgAAAABAYVQoEvytW7fqrbfe0qpVq9S0aVP16dNHf98aICAgQDVr1lSXLl00e/ZszZw5U0lJSZKkihUrysPDQ+Hh4Y72t99+uyTpl19+cTyfnJzs1Odvv/0mDw8PlS1bNj+HBwAAAABAvnN5gn/58mX17t1b/fv3V5s2bTRnzhzt2LFDs2fPvu4z15L/axvgNW/eXOnp6Tp27JijzZEjRyRJVatWlSQ1bdpUX3zxhVM/GzZsUIMGDeTp6ZmnYwIAAAAAoKC5fBf9IUOGaN26ddqzZ498fHwkSe+//75eeOEF7du3TwcOHNCZM2fUsGFD+fr66sCBAxoxYoRKlSqlzZuv7vaZmZnpuP/2228rMzNTgwYNkr+/vzZs2CDp6jF5d9xxh/r3769+/fpp69atGjBggD766CN17do1R7Fe272QXfQBAABQnLCLPlB45WYXfZcm+F9//bVat26thIQEtWjRwule+/btlZ6erjFjxujFF1/UgQMHZLPZFBQUpAcffFCjRo1SqVKlHO1Pnz6twYMHa8OGDfLx8dG9996rKVOmqEyZMk7ve/7557V//34FBgZq5MiRGjBgQI7jzc0fFgAAAACAW1VkEvyihgQfAAAAAFCQcpOHunwNPgAAAAAAuHUsJL8J3+6MkI+vu6vDAPJEy0Y7XR0CAAAAgDzADD4AAAAAAMVAkU/wMzIy1KxZsyw74VssFgUFBWnMmDE6efKkDMNwlBIlSigsLEyvvvqq2IIAAAAAAFAcFPkE393dXQsXLtT69eu1aNEiR/3gwYNVpkwZjR071lH35ZdfKikpST/99JMmTJig1157TfPmzXNF2AAAAAAA5Kkin+BLUvXq1RUXF6fBgwfr9OnTWrVqlZYsWaKFCxeqRIkSjnZly5ZVQECAqlatqkcffVTNmjXTDz/84MLIAQAAAADIG8Vmk73BgwdrxYoV6tWrl/bt26exY8eqfv36122/c+dO/fDDD+rdu/d129hsNtlsNse11WrNy5ABAAAAAMgzxWIGX5IMw9DMmTO1ceNGVahQQaNGjcrSplmzZvL19VWJEiXUsGFDPfzww+rVq9d1+4yLi5PZbHaUoKCg/BwCAAAAAAA3rdgk+JI0b948lSxZUidOnNCpU6ey3F+6dKl2796tPXv2aOnSpVq1alW2PwRcExMTI4vF4iiJiYn5GT4AAAAAADet2CT4W7du1VtvvaVVq1apadOm6tOnT5Yd8oOCghQWFqbbb79dDz/8sJ577jlNmTJFV65cybZPk8kkf39/pwIAAAAAQGFULBL8y5cvq3fv3urfv7/atGmjOXPmaMeOHZo9e/YNn3N3d1d6err+/PPPAooUAAAAAID8USw22Rs1apQyMzM1adIkSVKVKlU0ZcoUvfDCC+rQoYOj3dmzZ5WcnKz09HTt27dP77zzjqKiopiZBwAAAAAUeUU+wf/66681ffp0JSQkyMfHx1Hfr18/ffrpp+rTp4/mzJkjSWrTpo2kqzP3FStWVMeOHfXaa6+5JG4AAAAAAPKSYf/7QnVcl9VqldlslsViYdYfAAAAAJDvcpOHFos1+AAAAAAA/NuR4AMAAAAAUAwU+TX4rrB/V5R8fd1dHQb+os7d210dAgAAAAC4FDP4AAAAAAAUAy5L8DMyMtSsWTN17drVqd5isSgoKEhjxoyRJK1du1aRkZHy8/NTyZIl1bBhQy1YsMAFEQMAAAAAUHi5LMF3d3fXwoULtX79ei1atMhRP3jwYJUpU0Zjx47VtGnT1KVLFzVr1kzfffed9u7dqx49emjAgAEaNmyYq0IHAAAAAKDQcekn+tWrV1dcXJwGDx6s06dPa9WqVVqyZIkWLlyoM2fOaOjQoXruuecUGxurWrVqKSwsTEOHDtXrr7+uKVOm6LvvvpMkJSQkyDAMbdy4UQ0aNFDJkiXVrFkzHT582Ol9a9as0d133y0vLy+FhIRowoQJSk9Pd8XQAQAAAADIUy5fgz948GDVq1dPvXr10lNPPaWxY8eqfv36+vTTT5WWlpbtTH3//v3l6+urjz76yKn+xRdf1JQpU7Rz5055eHjoySefdNz7/PPP9dhjj+nZZ5/VgQMHNHv2bC1YsECvvfbadWOz2WyyWq1OBQAAAACAwsjlCb5hGJo5c6Y2btyoChUqaNSoUZKkI0eOyGw2q2LFilmeKVGihEJCQnTkyBGn+tdee00RERGqVauWRo0apS1btujKlSuOe6NGjVLv3r0VEhKitm3b6pVXXtHs2bOvG1tcXJzMZrOjBAUF5eHIAQAAAADIOy5P8CVp3rx5KlmypE6cOKFTp07l6Bm73S7DMJzq6tat6/jnaz8M/Pbbb5Kk77//Xi+//LJ8fX0dpV+/fkpKSlJqamq274iJiZHFYnGUxMTEmxkeAAAAAAD5zsPVAWzdulVvvfWW/ve//2ny5Mnq06ePvvzyS4WHh8tisej06dMKDAx0eubPP//U8ePH1apVK6d6T09Pxz9fS/4zMzMd/zthwgQ9+OCDWWLw8vLKNjaTySSTyXRL4wMAAAAAoCC4dAb/8uXL6t27t/r37682bdpozpw52rFjh2bPnq2uXbvKw8NDU6ZMyfLcrFmzlJKSokceeSTH77rrrrt0+PBhhYWFZSluboXiQwYAAAAAAG6aS2fwR40apczMTE2aNEmSVKVKFU2ZMkUvvPCCOnTooMmTJ2vYsGHy8vLS448/Lk9PT61atUqjR4/W0KFD1bhx4xy/a+zYserUqZOCgoLUrVs3ubm5ae/evdq3b59effXV/BoiAAAAAAAFwmUJ/tdff63p06crISFBPj4+jvp+/frp008/dXyqHxoaqjfeeEPvvPOOMjIyVLt2bc2cOVNPPPFErt7Xvn17rV27Vi+//LImT54sT09P1axZU3379s3roQEAAAAAUOAMu91ud3UQRYXVapXZbJbFYpG/v7+rwwEAAAAAFHO5yUNdvsleUXLttxCr1eriSAAAAAAA/wbX8s+czM2T4OfC2bNnJf1fe/ceFNV5vwH8WS5yZ1EoLATLpaAoIDFAGgNe4m20KqS5GC9BMkmnTQIKOq3aIoImSEISrUjQgSaajgaMBlKrCRGRGLUiKKxBAVEuoqkUaxEUkOv7+yPj+WWFXRdEVtfnM7Mznvd8zznvy3mG4fWcswcYOXKkjntCREREREREj5ObN29CLpdrrOEEvx9GjBgBAKirq7vnD5bobs3NzRg5ciQuX77MRzyo35gfGihmh+4H80MDxezQ/WB+VAkhcPPmzV6vj+8LJ/j9cOd1enK5nEGjAbO2tmZ+aMCYHxooZofuB/NDA8Xs0P1gfv6ftheY+QJ4IiIiIiIiIj3ACT4RERERERGRHuAEvx9MTEwQFxcHExMTXXeFHkHMD90P5ocGitmh+8H80EAxO3Q/mJ+BkwltvmufiIiIiIiIiB5qvIJPREREREREpAc4wSciIiIiIiLSA5zgExEREREREekBTvCJiIiIiIiI9AAn+P2QmpoKNzc3mJqawt/fH0ePHtV1l0jHEhMTERgYCCsrK9jb2+P555/H+fPnVWqEEIiPj4eTkxPMzMwwZcoUnDt3TqWmvb0dS5cuhZ2dHSwsLBASEoIrV64M5VBIxxITEyGTyRAdHS21MTukyY8//ohXX30Vtra2MDc3x5NPPonTp09L65kfUqerqwtr1qyBm5sbzMzM4O7ujvXr16Onp0eqYX4IAL7//nvMmzcPTk5OkMlk+Oqrr1TWD1ZOGhsbERYWBrlcDrlcjrCwMNy4ceMBj44eNE356ezsxKpVq+Dr6wsLCws4OTlhyZIl+Pe//62yD+an/zjB19Lu3bsRHR2NmJgYlJSUYOLEiZg9ezbq6up03TXSoSNHjiAiIgIFBQXIzc1FV1cXZs6ciZaWFqkmKSkJGzduREpKCoqKiqBQKDBjxgzcvHlTqomOjkZ2djYyMzNx7Ngx3Lp1C3PnzkV3d7cuhkVDrKioCGlpaRg3bpxKO7ND6jQ2NiIoKAjGxsb45ptvUFZWho8++gg2NjZSDfND6rz//vvYtm0bUlJSUF5ejqSkJHzwwQfYsmWLVMP8EAC0tLTAz88PKSkpfa4frJwsWrQISqUSOTk5yMnJgVKpRFhY2AMfHz1YmvLT2tqK4uJixMbGori4GFlZWaisrERISIhKHfMzAIK08vTTT4s333xTpc3Ly0usXr1aRz2ih1FDQ4MAII4cOSKEEKKnp0coFArx3nvvSTW3b98WcrlcbNu2TQghxI0bN4SxsbHIzMyUan788UdhYGAgcnJyhnYANORu3rwpPD09RW5urpg8ebKIiooSQjA7pNmqVatEcHCw2vXMD2kyZ84c8frrr6u0vfDCC+LVV18VQjA/1DcAIjs7W1oerJyUlZUJAKKgoECqOXHihAAgKioqHvCoaKjcnZ++FBYWCgDi0qVLQgjmZ6B4BV8LHR0dOH36NGbOnKnSPnPmTPzrX//SUa/oYdTU1AQAGDFiBACgpqYG9fX1KtkxMTHB5MmTpeycPn0anZ2dKjVOTk7w8fFhvh4DERERmDNnDqZPn67SzuyQJvv27UNAQABefvll2NvbY/z48UhPT5fWMz+kSXBwMPLy8lBZWQkAOHPmDI4dO4bf/OY3AJgf0s5g5eTEiROQy+X49a9/LdU888wzkMvlzNJjpqmpCTKZTLobjfkZGCNdd+BR8N///hfd3d1wcHBQaXdwcEB9fb2OekUPGyEEVqxYgeDgYPj4+ACAlI++snPp0iWpZtiwYRg+fHivGuZLv2VmZqK4uBhFRUW91jE7pEl1dTW2bt2KFStW4C9/+QsKCwuxbNkymJiYYMmSJcwPabRq1So0NTXBy8sLhoaG6O7uRkJCAhYuXAiAv39IO4OVk/r6etjb2/fav729PbP0GLl9+zZWr16NRYsWwdraGgDzM1Cc4PeDTCZTWRZC9Gqjx1dkZCR++OEHHDt2rNe6gWSH+dJvly9fRlRUFA4ePAhTU1O1dcwO9aWnpwcBAQHYsGEDAGD8+PE4d+4ctm7diiVLlkh1zA/1Zffu3di5cyc+//xzeHt7Q6lUIjo6Gk5OTggPD5fqmB/SxmDkpK96Zunx0dnZiQULFqCnpwepqan3rGd+NOMt+lqws7ODoaFhr/8Famho6PW/lvR4Wrp0Kfbt24f8/Hw4OztL7QqFAgA0ZkehUKCjowONjY1qa0j/nD59Gg0NDfD394eRkRGMjIxw5MgRJCcnw8jISDr3zA71xdHREWPHjlVpGzNmjPTFr/zdQ5r86U9/wurVq7FgwQL4+voiLCwMy5cvR2JiIgDmh7QzWDlRKBT4z3/+02v/165dY5YeA52dnZg/fz5qamqQm5srXb0HmJ+B4gRfC8OGDYO/vz9yc3NV2nNzc/Hss8/qqFf0MBBCIDIyEllZWTh8+DDc3NxU1ru5uUGhUKhkp6OjA0eOHJGy4+/vD2NjY5Waq1ev4uzZs8yXHps2bRpKS0uhVCqlT0BAABYvXgylUgl3d3dmh9QKCgrq9UrOyspKuLi4AODvHtKstbUVBgaqfwIaGhpKr8ljfkgbg5WTCRMmoKmpCYWFhVLNyZMn0dTUxCzpuTuT+wsXLuDQoUOwtbVVWc/8DNDQf6/foykzM1MYGxuLTz75RJSVlYno6GhhYWEhamtrdd010qG33npLyOVy8d1334mrV69Kn9bWVqnmvffeE3K5XGRlZYnS0lKxcOFC4ejoKJqbm6WaN998Uzg7O4tDhw6J4uJiMXXqVOHn5ye6urp0MSzSkZ9/i74QzA6pV1hYKIyMjERCQoK4cOGC2LVrlzA3Nxc7d+6UapgfUic8PFw88cQTYv/+/aKmpkZkZWUJOzs7sXLlSqmG+SEhfnrTS0lJiSgpKREAxMaNG0VJSYn0LeeDlZNZs2aJcePGiRMnTogTJ04IX19fMXfu3CEfLw0uTfnp7OwUISEhwtnZWSiVSpW/o9vb26V9MD/9xwl+P3z88cfCxcVFDBs2TDz11FPSq9Do8QWgz8/27dulmp6eHhEXFycUCoUwMTERkyZNEqWlpSr7aWtrE5GRkWLEiBHCzMxMzJ07V9TV1Q3xaEjX7p7gMzukyT//+U/h4+MjTExMhJeXl0hLS1NZz/yQOs3NzSIqKkr88pe/FKampsLd3V3ExMSo/FHN/JAQQuTn5/f5d054eLgQYvBycv36dbF48WJhZWUlrKysxOLFi0VjY+MQjZIeFE35qampUft3dH5+vrQP5qf/ZEIIMXT3CxARERERERHRg8Bn8ImIiIiIiIj0ACf4RERERERERHqAE3wiIiIiIiIiPcAJPhEREREREZEe4ASfiIiIiIiISA9wgk9ERERERESkBzjBJyIiIiIiItIDnOATERERERER6QFO8ImIiAaBTCbDV199pXX9a6+9hueff/6+jllbWwuZTAalUnlf+7mX+Ph4PPnkkw/0GB0dHfDw8MDx48cBDN3Y+nL3uZkyZQqio6OlZVdXV/z1r3+Vlvt77u/XSy+9hI0bNw7Z8YiI6NHBCT4REZEG9fX1iIqKgoeHB0xNTeHg4IDg4GBs27YNra2tuu7ePVVXV2PhwoVwcnKCqakpnJ2dERoaisrKSl13TUVaWhpcXFwQFBQEABg5ciSuXr0KHx+fIe/L5s2bsWPHDq3rr169itmzZz+4Dt1l7dq1SEhIQHNz85Adk4iIHg1Guu4AERHRw6q6uhpBQUGwsbHBhg0b4Ovri66uLlRWVuLTTz+Fk5MTQkJCdN1NtTo6OjBjxgx4eXkhKysLjo6OuHLlCr7++ms0NTXpunsqtmzZgvj4eGnZ0NAQCoVCJ32Ry+X9qh/qfo4bNw6urq7YtWsX3nrrrSE9NhERPdx4BZ+IiEiNt99+G0ZGRjh16hTmz5+PMWPGwNfXFy+++CIOHDiAefPmqd22tLQUU6dOhZmZGWxtbfH73/8et27d6lW3bt062Nvbw9raGn/4wx/Q0dEhrcvJyUFwcDBsbGxga2uLuXPnoqqqSuv+l5WVobq6GqmpqXjmmWekK+QJCQkIDAyU6latWoVRo0bB3Nwc7u7uiI2NRWdnp8Z9b9++HWPGjIGpqSm8vLyQmpoqrevo6EBkZCQcHR1hamoKV1dXJCYmqt1XcXExLl68iDlz5khtd9+i/91330EmkyEvLw8BAQEwNzfHs88+i/Pnz6vd7519fPHFF5g4cSLMzMwQGBiIyspKFBUVISAgAJaWlpg1axauXbsmbdffxyfuvkX/Xuf+zv4//PBDODo6wtbWFhERESo/89TUVHh6ekp3jbz00ksqxwwJCUFGRobWfSQioscDJ/hERER9uH79Og4ePIiIiAhYWFj0WSOTyfpsb21txaxZszB8+HAUFRVhz549OHToECIjI1Xq8vLyUF5ejvz8fGRkZCA7Oxvr1q2T1re0tGDFihUoKipCXl4eDAwM8Nvf/hY9PT1ajeEXv/gFDAwMsHfvXnR3d6uts7Kywo4dO1BWVobNmzcjPT0dmzZtUlufnp6OmJgYJCQkoLy8HBs2bEBsbCw+++wzAEBycjL27duHL774AufPn8fOnTvh6uqqdn/ff/89Ro0aBWtr63uOKSYmBh999BFOnToFIyMjvP766/fcJi4uDmvWrEFxcTGMjIywcOFCrFy5Eps3b8bRo0dRVVWFtWvX3nM/2tD23Ofn56Oqqgr5+fn47LPPsGPHDumxgFOnTmHZsmVYv349zp8/j5ycHEyaNEll+6effhqFhYVob28flH4TEZGeEERERNRLQUGBACCysrJU2m1tbYWFhYWwsLAQK1eulNoBiOzsbCGEEGlpaWL48OHi1q1b0voDBw4IAwMDUV9fL4QQIjw8XIwYMUK0tLRINVu3bhWWlpaiu7u7zz41NDQIAKK0tFQIIURNTY0AIEpKStSOIyUlRZibmwsrKyvx3HPPifXr14uqqiqNY09KShL+/v7SclxcnPDz85OWR44cKT7//HOVbd555x0xYcIEIYQQS5cuFVOnThU9PT0aj3NHVFSUmDp1qkrb3WPLz88XAMShQ4ekmgMHDggAoq2trc/93tnH3/72N6ktIyNDABB5eXlSW2Jiohg9erS0HB4eLkJDQ6XlyZMni6ioKGnZxcVFbNq0SVoeyLl3cXERXV1dUs3LL78sXnnlFSGEEF9++aWwtrYWzc3NfY5LCCHOnDkjAIja2lq1NURE9PjhFXwiIiIN7r5KX1hYCKVSCW9vb7VXT8vLy+Hn56dy5T8oKAg9PT0qt5T7+fnB3NxcWp4wYQJu3bqFy5cvAwCqqqqwaNEiuLu7w9raGm5ubgCAuro6rfsfERGB+vp67Ny5ExMmTMCePXvg7e2N3NxcqWbv3r0IDg6GQqGApaUlYmNj1R7j2rVruHz5Mt544w1YWlpKn3fffVd6fOC1116DUqnE6NGjsWzZMhw8eFBjH9va2mBqaqrVeMaNGyf929HREQDQ0NCg9TYODg4AAF9fX5W2e+1DW9qee29vbxgaGkrLjo6OUh9mzJgBFxcXuLu7IywsDLt27er1hY5mZmYA8Eh80SMREQ0dTvCJiIj64OHhAZlMhoqKCpV2d3d3eHh4SBOsvggh1N6+r669r5p58+bh+vXrSE9Px8mTJ3Hy5EkAUHlOXxtWVlYICQlBQkICzpw5g4kTJ+Ldd98FABQUFGDBggWYPXs29u/fj5KSEsTExKg9xp3HA9LT06FUKqXP2bNnUVBQAAB46qmnUFNTg3feeQdtbW2YP39+r2fIf87Ozg6NjY1ajcXY2Fj6952f070eWehrm7vbtH3s4V60Pfc/P/7dfbCyskJxcTEyMjLg6OiItWvXws/PDzdu3JDq//e//wH46TEMIiKiOzjBJyIi6oOtrS1mzJiBlJQUtLS09GvbsWPHQqlUqmx3/PhxGBgYYNSoUVLbmTNn0NbWJi0XFBTA0tISzs7OuH79OsrLy7FmzRpMmzYNY8aM0XoSrIlMJoOXl5fUt+PHj8PFxQUxMTEICAiAp6cnLl26pHZ7BwcHPPHEE6iuroaHh4fK584dBgBgbW2NV155Benp6di9eze+/PJLaVJ6t/Hjx6OiogJCiPsen65pe+7vxcjICNOnT0dSUhJ++OEH1NbW4vDhw9L6s2fPwtnZGXZ2doPafyIierRxgk9ERKRGamoqurq6EBAQgN27d6O8vFz60riKigqVW6x/bvHixTA1NUV4eDjOnj2L/Px8LF26FGFhYdIt4sBPV+LfeOMNlJWV4ZtvvkFcXBwiIyNhYGCA4cOHw9bWFmlpabh48SIOHz6MFStW9Kv/SqUSoaGh2Lt3L8rKynDx4kV88skn+PTTTxEaGgrgpzsV6urqkJmZiaqqKiQnJyM7O1vjfuPj45GYmIjNmzejsrISpaWl2L59OzZu3AgA2LRpEzIzM1FRUYHKykrs2bMHCoUCNjY2fe7vueeeQ0tLC86dO9ev8T2MtD33muzfvx/JyclQKpW4dOkS/v73v6OnpwejR4+Wao4ePYqZM2c+qGEQEdEjykjXHSAiInpY/epXv0JJSQk2bNiAP//5z7hy5QpMTEwwduxY/PGPf8Tbb7/d53bm5ub49ttvERUVhcDAQJibm+PFF1+UJsB3TJs2DZ6enpg0aRLa29uxYMEC6V3wBgYGyMzMxLJly+Dj44PRo0cjOTkZU6ZM0br/zs7OcHV1xbp166RXxt1ZXr58OQAgNDQUy5cvR2RkJNrb2zFnzhzExsaqvJP+br/73e9gbm6ODz74ACtXroSFhQV8fX0RHR0NALC0tMT777+PCxcuwNDQEIGBgfj6669hYND3dQVbW1u88MIL2LVrl8bX6T0KtD33mtjY2CArKwvx8fG4ffs2PD09kZGRAW9vbwDA7du3kZ2djW+//fZBDYOIiB5RMqEP98MRERHRI620tBTTp0/HxYsXYWVlpevuPNQ+/vhj/OMf/7jnlxcSEdHjh7foExERkc75+voiKSkJtbW1uu7KQ8/Y2BhbtmzRdTeIiOghxCv4RERERERERHqAV/CJiIiIiIiI9AAn+ERERERERER6gBN8IiIiIiIiIj3ACT4RERERERGRHuAEn4iIiIiIiEgPcIJPREREREREpAc4wSciIiIiIiLSA5zgExEREREREekBTvCJiIiIiIiI9MD/AWh6UpLfl5VCAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sales by Genre\n",
    "sales_by_genre = df.groupby('Genre')['Global_Sales'].sum().reset_index()\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data=sales_by_genre, x='Global_Sales', y='Genre', palette='viridis')\n",
    "plt.title('Global Sales by Genre')\n",
    "plt.xlabel('Global Sales (in millions)')\n",
    "plt.ylabel('Genre')\n",
    "plt.show()\n",
    "\n",
    "# Sales by Platform\n",
    "sales_by_platform = df.groupby('Platform')['Global_Sales'].sum().reset_index()\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data=sales_by_platform, x='Global_Sales', y='Platform', palette='viridis')\n",
    "plt.title('Global Sales by Platform')\n",
    "plt.xlabel('Global Sales (in millions)')\n",
    "plt.ylabel('Platform')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "3179fc86-6fa9-4bf4-9713-a173cb9487c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Sales by Publisher\n",
    "sales_by_publisher = df.groupby('Publisher')['Global_Sales'].sum().nlargest(10).reset_index()\n",
    "\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.barplot(data=sales_by_publisher, x='Global_Sales', y='Publisher', palette='viridis')\n",
    "plt.title('Top 10 Publishers by Global Sales')\n",
    "plt.xlabel('Global Sales (in millions)')\n",
    "plt.ylabel('Publisher')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f2b2e4e9-1de1-46a2-98b7-501b51808437",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}