1.A Simple Starting Point on Viz Stats in Python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Simple Starting Point\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import relevant modules\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "--2023-11-13 19:11:31--  https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 322 [text/plain]\n",
      "Saving to: 'grades.csv'\n",
      "\n",
      "     0K                                                       100% 2.37M=0s\n",
      "\n",
      "2023-11-13 19:11:32 (2.37 MB/s) - 'grades.csv' saved [322/322]\n",
      "\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>Name</th>\n",
       "      <th>StudyHours</th>\n",
       "      <th>Grade</th>\n",
       "      <th>Pass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dan</td>\n",
       "      <td>10.00</td>\n",
       "      <td>50.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Joann</td>\n",
       "      <td>11.50</td>\n",
       "      <td>50.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Pedro</td>\n",
       "      <td>9.00</td>\n",
       "      <td>47.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Rosie</td>\n",
       "      <td>16.00</td>\n",
       "      <td>97.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ethan</td>\n",
       "      <td>9.25</td>\n",
       "      <td>49.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Vicky</td>\n",
       "      <td>1.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Frederic</td>\n",
       "      <td>11.50</td>\n",
       "      <td>53.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Jimmie</td>\n",
       "      <td>9.00</td>\n",
       "      <td>42.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Rhonda</td>\n",
       "      <td>8.50</td>\n",
       "      <td>26.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Giovanni</td>\n",
       "      <td>14.50</td>\n",
       "      <td>74.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Francesca</td>\n",
       "      <td>15.50</td>\n",
       "      <td>82.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Rajab</td>\n",
       "      <td>13.75</td>\n",
       "      <td>62.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Naiyana</td>\n",
       "      <td>9.00</td>\n",
       "      <td>37.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Kian</td>\n",
       "      <td>8.00</td>\n",
       "      <td>15.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Jenny</td>\n",
       "      <td>15.50</td>\n",
       "      <td>70.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Jakeem</td>\n",
       "      <td>8.00</td>\n",
       "      <td>27.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Helena</td>\n",
       "      <td>9.00</td>\n",
       "      <td>36.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Ismat</td>\n",
       "      <td>6.00</td>\n",
       "      <td>35.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Anila</td>\n",
       "      <td>10.00</td>\n",
       "      <td>48.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Skye</td>\n",
       "      <td>12.00</td>\n",
       "      <td>52.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Daniel</td>\n",
       "      <td>12.50</td>\n",
       "      <td>63.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Aisha</td>\n",
       "      <td>12.00</td>\n",
       "      <td>64.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Name  StudyHours  Grade   Pass\n",
       "0         Dan       10.00   50.0  False\n",
       "1       Joann       11.50   50.0  False\n",
       "2       Pedro        9.00   47.0  False\n",
       "3       Rosie       16.00   97.0   True\n",
       "4       Ethan        9.25   49.0  False\n",
       "5       Vicky        1.00    3.0  False\n",
       "6    Frederic       11.50   53.0  False\n",
       "7      Jimmie        9.00   42.0  False\n",
       "8      Rhonda        8.50   26.0  False\n",
       "9    Giovanni       14.50   74.0   True\n",
       "10  Francesca       15.50   82.0   True\n",
       "11      Rajab       13.75   62.0   True\n",
       "12    Naiyana        9.00   37.0  False\n",
       "13       Kian        8.00   15.0  False\n",
       "14      Jenny       15.50   70.0   True\n",
       "15     Jakeem        8.00   27.0  False\n",
       "16     Helena        9.00   36.0  False\n",
       "17      Ismat        6.00   35.0  False\n",
       "18      Anila       10.00   48.0  False\n",
       "19       Skye       12.00   52.0  False\n",
       "20     Daniel       12.50   63.0   True\n",
       "21      Aisha       12.00   64.0   True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Get,Read and Clean the Data\n",
    "\n",
    "!wget https://raw.githubusercontent.com/MicrosoftDocs/mslearn-introduction-to-machine-learning/main/Data/ml-basics/grades.csv\n",
    "\n",
    "df_students = pd.read_csv('grades.csv')\n",
    "\n",
    "df_students = df_students.dropna(axis=0,how='any')\n",
    "\n",
    "passes = pd.Series(df_students['Grade']>=60)\n",
    "\n",
    "df_students = pd.concat([df_students,passes.rename('Pass')],axis=1)\n",
    "\n",
    "df_students"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize Data with Bar Chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "plt.bar(x=df_students.Name,height=df_students.Grade,color='orange')\n",
    "\n",
    "plt.title('Student Grades')\n",
    "plt.xlabel('Student Names')\n",
    "plt.ylabel('Student Grades')\n",
    "plt.grid(color='#95a5a6',linestyle='--',linewidth=2,axis='y',alpha=0.7)\n",
    "plt.xticks(rotation=90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Working With Subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_6784\\2271221588.py:5: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
      "  ax[0].set_xticklabels(df_students.Name,rotation=90)\n",
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_6784\\2271221588.py:15: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,2,figsize=(9,5))\n",
    "\n",
    "ax[0].bar(x=df_students.Name,height=df_students.Grade,color='orange')\n",
    "ax[0].set_title('Grades')\n",
    "ax[0].set_xticklabels(df_students.Name,rotation=90)\n",
    "\n",
    "\n",
    "pass_counts = df_students.Pass.value_counts()\n",
    "ax[1].pie(pass_counts,labels=pass_counts)\n",
    "ax[1].set_title('Passing Grades')\n",
    "ax[1].legend(pass_counts.keys().tolist())\n",
    "\n",
    "fig.suptitle('Student Data')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualizing Directly With Pandas DataFrame. i.e. without import matplotlib \n",
    "N.B.: Does not work if data contains NaN values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Name'>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_students.plot.bar(x='Name',y='StudyHours',color='teal',figsize=(9,6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Distribution with Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_6784\\647587441.py:11: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var_students = df_students['Grade']\n",
    "\n",
    "fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "plt.hist(var_students)\n",
    "\n",
    "plt.title('Student Grade Data Distribution')\n",
    "plt.xlabel('Value')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Measures of Central Tendency i.e. Mean, Mode, Median,Min,Max etc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum:3.00\n",
      "Maximum:97.00\n",
      "Mean:49.18\n",
      "Median:49.50\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var = df_students['Grade']\n",
    "\n",
    "min_val = var.min()\n",
    "max_val = var.max()\n",
    "mean_val = var.mean()\n",
    "median_val = var.median()\n",
    "\n",
    "print('Minimum:{:.2f}\\nMaximum:{:.2f}\\nMean:{:.2f}\\nMedian:{:.2f}'.format(min_val,max_val,mean_val,median_val))\n",
    "\n",
    "fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "plt.hist(var)\n",
    "\n",
    "plt.axvline(x=min_val,color='gray',linestyle='dashed',linewidth=2)\n",
    "plt.axvline(x=max_val,color='black',linestyle='dashed',linewidth=2)\n",
    "plt.axvline(x=mean_val,color='green',linestyle='dashed',linewidth=2)\n",
    "plt.axvline(x=median_val,color='red',linestyle='dashed',linewidth=2)\n",
    "\n",
    "plt.title('Student Data Distribution')\n",
    "plt.xlabel('Value')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Distribution with Boxplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_6784\\2644967597.py:9: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "var = df_students.Grade\n",
    "\n",
    "fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "plt.boxplot(var)\n",
    "\n",
    "plt.title('Data Distribution')\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To get clearer picture of the Data Distribution we write a function that combines Histogram with Boxplot as subplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum:3.00\n",
      "Maximum:97.00\n",
      "Mean:49.18\n",
      "Median:49.50\n",
      "Mode:50.00\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Admin\\AppData\\Local\\Temp\\ipykernel_6784\\4007849469.py:28: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_distribution(var_data):\n",
    "    import matplotlib.pyplot as plt\n",
    "\n",
    "    min_val = var_data.min()\n",
    "    max_val = var_data.max()\n",
    "    mean_val = var_data.mean()\n",
    "    median_val = var_data.median()\n",
    "    mode_val = var_data.mode()[0]\n",
    "\n",
    "    print('Minimum:{:.2f}\\nMaximum:{:.2f}\\nMean:{:.2f}\\nMedian:{:.2f}\\nMode:{:.2f}'.format(min_val,max_val,mean_val,median_val,mode_val))\n",
    "\n",
    "    fig,ax = plt.subplots(2,1,figsize=(9,6))\n",
    "\n",
    "    ax[0].hist(var_data)\n",
    "    ax[0].set_ylabel('Frequency')\n",
    "\n",
    "    ax[0].axvline(x=min_val,color='gray',linestyle='dashed',linewidth=2)\n",
    "    ax[0].axvline(x=max_val,color='green',linestyle='dashed',linewidth=2)\n",
    "    ax[0].axvline(x=mean_val,color='red',linestyle='dashed',linewidth=2)\n",
    "    ax[0].axvline(x=median_val,color='blue',linestyle='dashed',linewidth=2)\n",
    "    ax[0].axvline(x=mode_val,color='yellow',linestyle='dashed',linewidth=2)\n",
    "\n",
    "    ax[1].boxplot(var_data,vert=False)\n",
    "    ax[1].set_xlabel('Value')\n",
    "\n",
    "    fig.suptitle('Data Distribution')\n",
    "\n",
    "    fig.show()\n",
    "\n",
    "col = df_students['Grade']\n",
    "\n",
    "show_distribution(col)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize Probability Density"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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D7r77bkfBUWn16tUEBQXRqVMn7r33XjIyMs55reLiYnJzc6vcRETk/OQUlXLn/PKCI9jXk/9NHnTOggMgDugUF8clK1ZAuxRgBRBHM08Lc/7Yh/EDI7Db4ekvd/L5lqMX42mIiEg1DCs6MjMzsVqtBAdX3dowODiY9PT0au+Tnp5ebf+ysjIyMzNrlePLL78kOzubiRMnVmkfOXIkH374IatWreLVV19l48aNXHnllRQXF5/1WjNmzMDPz89xa926da0yiYg0NqdLrfxp4Sb2pOcR6OPJ/+4bTKdgnwu6ppvZxPPXd+euS9sC8Mhn21m153gdpBURkZoyfCH5b0cX7Hb7GW2/17+69vM1b948Ro4cSVhYWJX2cePGMXr0aKKiorjuuutYvnw5+/btY+nSpWe91hNPPEFOTo7jlpKSUqtMIiKNzTNf7WT94ZP4eFp4/67+tPH3rpPrmkwmnh7djZt6t8Jqs/PQx1s5kJFfJ9cWEZHzZ1jRERAQgJub2xmjGhkZGWeMZlQKCQmptr/FYsHf37/GGZKSkli5ciWTJk363b6hoaFERESwf//+s/bx9PTE19e3yk1ERM7tkw3JfLrpKGYTzL2jD93C6vZnp9lsYubNlzAgsiX5xWX86b+byDtduym5IiJSO4YVHR4eHkRHRzt2jqoUGxvL4MGDq73PoEGDzui/YsUK+vbti7t7zfdiX7BgAUFBQYwePfp3+2ZlZZGSkkJoaGiNH0dERKq3+1guzyzZBcBfYzozpGNgvTyOu5uZOX/sQ6ifF4dOFPD44h3obFwRkYvH0OlV06ZN491332X+/PkkJiYydepUkpOTmTx5MlA+XenOO+909J88eTJJSUlMmzaNxMRE5s+fz7x585g+fbqjT0lJCVu3bmXr1q2UlJSQmprK1q1bOXDgQJXHttlsLFiwgAkTJmCxVD0jMT8/n+nTpxMfH8+RI0dYvXo11113HQEBAdx44431+IqIiDQexWVWpi7aSkmZjau6BPHnoe3r9fECmnnyxh3RWMwmlu5I44uE1Hp9PBER+YWhJ5KPGzeOrKwsnn/+edLS0oiKimLZsmVERJRva5iWllblzI7IyEiWLVvG1KlTmTNnDmFhYbz22muMHTvW0efYsWP07t3b8fUrr7zCK6+8wtChQ1m9erWjfeXKlSQnJ3P33XefkcvNzY0dO3awcOFCsrOzCQ0N5YorrmDRokX4+FzYwkYRESn3f7H72Xs8D/+mHrx08yWYzbVbm1cTvVo3Z8rVHXllxT6e+WoX/dq2pHXLulk/IiIiZ2foOR0Nnc7pEBGp3raUbG6c+zM2O7w1Pprh3as/zPX3hAPrwsMJT02FY2YItQGtgLNvj1tmtTHu7XVsTjrFkI4BLLy7f603IxERaaxc5pwOERFpnKw2O09/tRObHa7vFVbrgqO2LG5mXrmlJx4WM2v2Z/L19rSL+vgiIo2Rig4REbmoFm1MYfvRHHw8LTw1uusFXeteYOe99xI/dSrsvRyYWtF6bpEBTXlgWAcAnv96NzlF2s1KRKQ+GbqmQ0REGpeTBSW89N0eAKbFdCLIx+uCrvd3gL//vVb3nTysHV9tTeVQZgGvfLeXF26IuqAsIiJydhrpEBGRi+bl7/aSXVhKlxAfxg+MMDSLp8WNf9xYXmh8sD6JXcdyDM0jItKQqegQEZGL4kBGHos2lu9I+MINUVjcjP8VNLh9ANdeEordDv9avsfoOCIiDZbxP/FFRKRReOW7fdjsENMtmH5tWxodx+HR4V1wdzOxZn8mP+47YXQcEZEGSUWHiIjUu4TkU3y7Kx2zCR4Z3rnOrhsOHA0PB5MJ0twAU0Xr+Wvj7834gW0BmLF8D1abdpIXEalrKjpERKRe2e12Zn5bPnVpbJ9wOgY73yGrf7myAz5eFhLTcnVSuYhIPVDRISIi9eqnA5msO3QSD4uZKdd0MjpOtVo09eCBK8q30H3t+/2UWm0GJxIRaVhUdIiISL36z6oDANzevw2tmjcxOM3ZTRjUloBmHiSfLNRoh4hIHVPRISIi9WbD4ZNsOHwSDzcz9w1tZ3Scc2ri4cafLi/POOeHA5RptENEpM6o6BARkXrz+g/loxxjo8MJ9XPeUY5KdwyMwL+pB0lZGu0QEalLKjpERKRebD+azY/7TuBmNvHnoe2NjnNevD0s3Fsx2vG6RjtEROqMig4REakXc384CMD1PcNo4+9tcJrzN35gBC0rRjuW7Uw3Oo6ISIOgokNEROrckcwCvttd/ob9z8NcY5SjUlNPC3cOigDg7R8PYrfr3A4RkQulokNEROrce2uPYLfDFZ0DnfJcjt9z56C2eLmb2ZmaS/zBLKPjiIi4PBUdIiJSp3KKSvl0UwoA91xWvztWfQAc++ADtn37LRx/Ffi2ovXCtGzqwS3RrQF468dDF3w9EZHGzmJ0ABERaVg+2ZBMYYmVLiE+XNrBv14faxjAsGEVXw2v02tPGhLJh+uTiNt3gj3puXQJ8a3T64uINCYa6RARkTpTZrXx/tojANx9aSQmk8nYQBcgwr8pI6JCAHjnx8MGpxERcW0qOkREpM58t+s4x3JOE9DMgzG9woyOc8EmDSmfHvb19mNk5RcbnEZExHWp6BARkTrzwbokAG7v3wYvd7d6f7zVwIbVq9n23XewdTbwXUVr3ejdujmXhPtRUmZjUcU6FRERqTkVHSIiUicOZOQTfygLswlu7d/mojzmHUDYHXfQc8QICP4rMKKitW6YTCbuHNQWgA/XJeuwQBGRWlLRISIideLjDckAXNklmLDmTQxOU3euvSSUFt7upGYX8f2eDKPjiIi4JBUdIiJywU6XWvls81EA/jjw4oxyXCxe7m6OkZuF8UeMDSMi4qJUdIiIyAVbuj2NnKJSWjVvwuUdA42OU+f+OKANZhP8fCCLAxl5RscREXE5KjpEROSCfbi+YgH5gDa4mV13m9yzCW/hzVVdgwFYGJ9kcBoREdejokNERC7I7mO5bEnOxmI2cUvfcKPj1JsJFQvKF28+SkFxmbFhRERcjIoOERG5IJULyId3DyHIx8vgNPVncHt/Ivy9KSixsnRHmtFxRERciooOERGptdOlVr7amgrAuH6tDU5Tv8xmk+M5LtqoMztERGpCRYeIiNTaysTj5J4uI9TPi0s7BBgdp97d3CccN7OJzUmn2H9cC8pFRM6Xig4REam1ym1yx1a8GW/ogny9uLJLEKDRDhGRmlDRISIitZKec5of950AYGy0MQvIjwLhR4+C3Q6hVsBe0Vp/butfPsXq84RUisus9fpYIiINhYoOERGplS8SUrHZoW9ECyIDmhod56K5vGMgIb5enCwoIXb3caPjiIi4BBUdIiJSY3a7nc82l08vasjb5FbH4mZ2PGdNsRIROT8qOkREpMYSUrI5eKIAL3czo3qEGh3novtD39aYTLBmfyZHTxUaHUdExOmp6BARkRqrXEA+MioUHy93w3I8B3z73HPET5sGq68AplW01q/WLb0ZGOkPwFdbj9X744mIuDoVHSIiUiPFZVaWbi8/HG9sH2OnVr0DRL3zDoP+7/+g84/A/1W01r+b+rQCYPGWo9jt9ovymCIirkpFh4iI1MiP+zLJKSolyMeTQe39jY5jmJE9QvFyN3PoRAHbjuYYHUdExKmp6BARkRqpPIH8up5hjeJsjrNp5mlhRPcQAD7fUr/b9IqIuDoVHSIict7yi8tYmVi+Tez1vcIMTmO8myqml3297RglZTaD04iIOC8VHSIict5id6dzutRGZEBTerTyMzqO4S7tEECQjyenCktZvTfD6DgiIk5LRYeIiJy3yp2axvQMw2RqvFOrKrmZTdzYu3xB+edbUg1OIyLivFR0iIjIecnKL2bN/kwAxmhqlUPlFKvv9xwnu7DE4DQiIs5JRYeIiJyXZTvTsdrs9GjlR/vAZkbHcRqdQ3zoFupLqdXO1xVbCYuISFUqOkRE5Lwsqdi1SgvIz1R5Zod2sRIRqZ6KDhER+V1HTxWy8cgpTCa49hLnKTqGAvuGDmV7TAwcag3EVLReXGN6hWE2QUJyNiknCy/644uIODuL0QFERMT5fb2tfNrQwEh/Qvy8DE7ziw8BPvzQ6BgE+XgxqL0/Px/IYsm2YzxwRQejI4mIOBWNdIiIyO9auqN816rrejrPKIezGVPx2ny97ZjBSUREnI/hRcfcuXOJjIzEy8uL6Oho1qxZc87+cXFxREdH4+XlRbt27XjzzTerfH/Xrl2MHTuWtm3bYjKZmD179hnXePbZZzGZTFVuISEhVfrY7XaeffZZwsLCaNKkCcOGDWPXrl0X/HxFRFxNclYhO1NzcTObGBEV8vt3aKRGdA/F3c3EnvQ89h/PMzqOiIhTMbToWLRoEVOmTOGpp54iISGBIUOGMHLkSJKTk6vtf/jwYUaNGsWQIUNISEjgySef5KGHHmLx4sWOPoWFhbRr145//etfZxQSv9a9e3fS0tIctx07dlT5/ksvvcSsWbN4/fXX2bhxIyEhIVxzzTXk5ekXiYg0Lst2VkytateSlk09DE7jvPy83RnaKRDQaIeIyG8ZWnTMmjWLe+65h0mTJtG1a1dmz55N69ateeONN6rt/+abb9KmTRtmz55N165dmTRpEnfffTevvPKKo0+/fv14+eWXufXWW/H09DzrY1ssFkJCQhy3wMBAx/fsdjuzZ8/mqaee4qabbiIqKor333+fwsJCPvroo7p7AUREXMDyHeVFx6geoQYnOdOVwPorr+RI9+6Q0ALoXtFqjMrpZ19vT8NutxuWQ0TE2RhWdJSUlLB582ZiYmKqtMfExLB27dpq7xMfH39G/+HDh7Np0yZKS0tr9Pj79+8nLCyMyMhIbr31Vg4dOuT43uHDh0lPT6/yWJ6engwdOvSs2QCKi4vJzc2tchMRcWUpJwvZdjQHswmGd3e+qVX7gFb79tF2924IyQV2V7Qa4+quwXi5mzmcWcDOVP0OEBGpZFjRkZmZidVqJTg4uEp7cHAw6enp1d4nPT292v5lZWVkZmae92MPGDCAhQsX8t133/HOO++Qnp7O4MGDycrKcjxO5bXPNxvAjBkz8PPzc9xat2593plERJzRtzvLf+YNiPQnoNnZR4+lXFNPC1d1Lf/d8fV2TbESEalk+EJyk8lU5Wu73X5G2+/1r679XEaOHMnYsWPp0aMHV199NUuXLgXg/fffv6BsTzzxBDk5OY5bSkrKeWcSEXFGSx1Tq5xvlMNZ/XoXK5tNU6xERMDAoiMgIAA3N7czRg4yMjLOGGGoFBISUm1/i8WCv79/rbM0bdqUHj16sH//fsfjADXKBuVTsHx9favcRERcVWp2EVtTsjGZYLh2rTpvQzsF4uNpIS3nNJuTTxkdR0TEKRhWdHh4eBAdHU1sbGyV9tjYWAYPHlztfQYNGnRG/xUrVtC3b1/c3d1rnaW4uJjExERCQ8sXSUZGRhISElLlsUpKSoiLiztrNhGRhqZyAXm/ti0J8nGeAwGdnZe7GzEV61+WbNUUKxERMHh61bRp03j33XeZP38+iYmJTJ06leTkZCZPngyUT1e68847Hf0nT55MUlIS06ZNIzExkfnz5zNv3jymT5/u6FNSUsLWrVvZunUrJSUlpKamsnXrVg4cOODoM336dOLi4jh8+DDr16/n5ptvJjc3lwkTJgDl06qmTJnCiy++yBdffMHOnTuZOHEi3t7e3H777Rfp1RERMdbyivUco51w1ypnN6ZX+RSrZTvSKLPaDE4jImI8i5EPPm7cOLKysnj++edJS0sjKiqKZcuWERERAUBaWlqVMzsiIyNZtmwZU6dOZc6cOYSFhfHaa68xduxYR59jx47Ru3dvx9evvPIKr7zyCkOHDmX16tUAHD16lNtuu43MzEwCAwMZOHAg69atczwuwKOPPkpRURH3338/p06dYsCAAaxYsQIfH596flVERIyXllPE5qRTmEzoQMBaGNzen5ZNPcgqKCH+UBZDOgb+/p1ERBowk10bideb3Nxc/Pz8yMnJ0foOEXEpC34+zHNf76Zf2xb8b7LzTisNB9aFhxOemgrHzBBqA1oBRw1OBk9+sYOP1idzW/82zLiph9FxRETqVE3f5xq+e5WIiDifZU58IKCrGBVV/tqt2JWuKVYi0ugZOr1KREScT0beaTYlle+65OxTq54BEp95hpT8fAbt3wKhfYBmRscCYGC7lrTwdieroIQNh08yuEOA0ZFERAyjokNERKpYuTsDux16tW5OqF8To+Oc058A/vQno2NUy+JmZnj3ED7ZmMKynWkqOkSkUdP0KhERqWLF7vJdq2K6n/1cIjk/Iyump3278zhWHRQoIo2Yig4REXHIO13K2gNZAMR0c+6pVa5gcHt//Jq4k5lfzKYjJ42OIyJiGBUdIiLiELfvBCVWG+0Cm9IhyDnWRpxLGnAsLY3jR4/C8a2U71qVZmyoX3F3M3NNt/IRo8pzT0REGiMVHSIi4rBi13HAdUY5+gG2fv0Ibt0abNFA64pW5zGqR/lruXxnGjZNsRKRRkpFh4iIAFBSZuOHPRmA1nPUpUs7BODjaeF4bjEJKaeMjiMiYggVHSIiAkD8oSzyissI9PGkV3hzo+M0GJ4WN66umGK1bIemWIlI46SiQ0REgPJD7ACu6RaM2WwyOE3DMrLivJPlOzTFSkQaJxUdIiKCzWYndnf5eo7h3V1jPYcrubxTIE093DiWc5ptR7ONjiMictGp6BAREbYdzSYjrxgfTwuD2vkbHafB8XJ348qu2sVKRBovFR0iIsJ3FbtWDesShIdFvxrqw6iKKVbLdqRht2uKlYg0LvrNIiIiv5xC3k27VtWXYZ2DaOLuxtFTRexIzTE6jojIRaWiQ0SkkTuQkc+hEwW4u5kY1jnQ6DgNVhMPN67oUv76fqspViLSyKjoEBFp5CpHOQa3D8DHy93gNA1b5SL973ap6BCRxsVidAARETGW4xRyFzwQ8Hug6PvvOVxWRmRRMtAGZ/7VdkWXINzdTBw8UcCBjHw6BDUzOpKIyEXhvD+ZRUSk3mXknmZrSjYA13R1vaKjM0DnzhVfdTcwyfnx9XJnUPsAftx3gu92pdMhqIPRkURELgpNrxIRacRW7ckAoGfr5gT5ehmcpnEYXjGitEJTrESkEVHRISLSiH1fUXRc1SXI4CSNxzXdgjGZYNvRHNJyioyOIyJyUajoEBFppE6XWvlpfyYAV3V1zaLjI+CHjz5i/bvvws8PAO9WtDqvIB8v+rRpAfyynkZEpKHTmg4RkUZq3aEsikqthPh60S3U1+g4tfIosO7RRwlPTYVjZsAGtAJuNzbY7xjePZjNSaf4blc6Ewa3NTqOiEi900iHiEgjVbme48quQZhMJoPTNC6VW+euP3ySUwUlBqcREal/KjpERBohu93O94laz2GUCP+mdAnxwWqzO9bViIg0ZCo6REQaoX3H80nNLsLTYmZw+wCj4zRKMRWjHdrFSkQaAxUdIiKN0MrE8gXMl3YIoImHm8FpGqfKrXN/3H+CohKrwWlEROqXig4RkUbIsZ5DU6sM0y3Ul/AWTThdaiNu3wmj44iI1CsVHSIijczJghK2JJ8CVHQYyWQyORaUa4qViDR0KjpERBqZ1XszsNuha6gvYc2bGB2nUassOlYmHqfUajM4jYhI/VHRISLSyFTulnS1ix4I2JBER7QgoJkHuafLWH/opNFxRETqjYoOEZFGpNRq48e95esHGsLUqhAgKySE461awSkvyg8GDDE41flzM5u4plv5gvLvNMVKRBowFR0iIo3IxiMnySsuw7+pBz3Dmxsd54JtAnpu2kTw0aPQrQA4WtHqOhxb5+5Ox2azG5xGRKR+qOgQEWlEVlUcCHhFlyDMZp1C7gwGt/enmaeF47nFbDuabXQcEZF6oaJDRKQRqdwqV6eQOw9PixtXVPz3+G7XcYPTiIjUDxUdIiKNxKET+RzKLMDdzcRlHXUKuTOpPChQW+eKSEOlokNEpJGoHOUYEOmPj5e7wWnqxn1A7H33sfmWW+DHrsAtFa2uZWinQDzczBzKLOBARr7RcURE6pyKDhGRRuL7xIZ3CvlSoOvSpUR/9hl03Ad8VtHqWny83BncwR8oX1AuItLQqOgQEWkEcopK2Xik/ByIq3Q+h1OK6Va+i5XWdYhIQ6SiQ0SkEViz/wRlNjvtA5sS4d/U6DhSjau7BWEywbaUbNJzThsdR0SkTqnoEBFpBCq3yr26a7DBSeRsgny86N26OQCxiRrtEJGGRUWHiEgDZ7XZ+WFvw1vP0RANrzwoULtYiUgDo6JDRKSB25pyilOFpfh6WYiOaGF0HDmHytPJ4w9mkVNUanAaEZG6o6JDRKSBq9y1aljnICxu+rHvzCIDmtIxqBllNjurK0anREQaAv32ERFp4CqLDu1a5RpiKg8K3K11HSLScKjoEBFpwFJOFrL3eB5mU/kBdOL8KrfOXb0ng+Iyq8FpRETqhsXoACIiUn8qF5D3jWhJc28Pg9PUvduAnbfdRuqpUwzYuw1CewKuvW6lRys/Qny9SM89zdqDWVzRWSNUIuL6VHSIiDRgjlPIG+jUqpcBXn7Z6Bh1ymw2cU23YP67LokVu46r6BCRBkHTq0REGqiC4jLiD2YBcJW2ynUples6Yncfx2azG5xGROTCGV50zJ07l8jISLy8vIiOjmbNmjXn7B8XF0d0dDReXl60a9eON998s8r3d+3axdixY2nbti0mk4nZs2efcY0ZM2bQr18/fHx8CAoK4oYbbmDv3r1V+kycOBGTyVTlNnDgwAt+viIiF8vPBzIpsdpo09KbDkHNjI4jNTAg0h8fLwuZ+cUkpGQbHUdE5IIZWnQsWrSIKVOm8NRTT5GQkMCQIUMYOXIkycnJ1fY/fPgwo0aNYsiQISQkJPDkk0/y0EMPsXjxYkefwsJC2rVrx7/+9S9CQkKqvU5cXBwPPPAA69atIzY2lrKyMmJiYigoKKjSb8SIEaSlpTluy5Ytq7snLyJSz1bt+eVAQJPJZHAaqQkPi9lxkOOK3TooUERcn8lutxs2bjtgwAD69OnDG2+84Wjr2rUrN9xwAzNmzDij/2OPPcaSJUtITEx0tE2ePJlt27YRHx9/Rv+2bdsyZcoUpkyZcs4cJ06cICgoiLi4OC6//HKgfKQjOzubL7/8snZPDsjNzcXPz4+cnBx8fX1rfR0RkZqy2ewMnPE9GXnF/Pee/gzp2DB3ruoCLOnShbBjx2i2tRjaeQJhwB6Dk124pdvTeOCjLUQGNGXVX4eqcBQRp1LT97mGjXSUlJSwefNmYmJiqrTHxMSwdu3aau8THx9/Rv/hw4ezadMmSktrf3JrTk4OAC1btqzSvnr1aoKCgujUqRP33nsvGRk6qElEXMOuY7lk5BXT1MON/pEtf/8OLiof8M7Pp1leHjQpA/IqWl3f0M6BeLiZOZxZwIGMhvGcRKTxMqzoyMzMxGq1EhwcXKU9ODiY9PTqh5LT09Or7V9WVkZmZmatctjtdqZNm8Zll11GVFSUo33kyJF8+OGHrFq1ildffZWNGzdy5ZVXUlxcfNZrFRcXk5ubW+UmImKE7/eUHyw3pGMgnhY3g9NIbTTztHBpB39ABwWKiOszfCH5b4eL7Xb7OYeQq+tfXfv5evDBB9m+fTsff/xxlfZx48YxevRooqKiuO6661i+fDn79u1j6dKlZ73WjBkz8PPzc9xat25dq0wiIheqoW+V21jEdC9fm7hil9Z1iIhrM6zoCAgIwM3N7YxRjYyMjDNGMyqFhIRU299iseDv71/jDH/5y19YsmQJP/zwA+Hh4efsGxoaSkREBPv37z9rnyeeeIKcnBzHLSUlpcaZREQu1PHc0+xILZ82qjMeXNvVXYMxmWDb0RzScoqMjiMiUmuGFR0eHh5ER0cTGxtbpT02NpbBgwdXe59Bgwad0X/FihX07dsXd3f3835su93Ogw8+yOeff86qVauIjIz83ftkZWWRkpJCaGjoWft4enri6+tb5SYicrH9ULFrVc/WzQn08TQ4jVyIQB9PotuUn7C+UlOsRMSFGTq9atq0abz77rvMnz+fxMREpk6dSnJyMpMnTwbKRw7uvPNOR//JkyeTlJTEtGnTSExMZP78+cybN4/p06c7+pSUlLB161a2bt1KSUkJqampbN26lQMHDjj6PPDAA3zwwQd89NFH+Pj4kJ6eTnp6OkVF5Z8i5efnM336dOLj4zly5AirV6/muuuuIyAggBtvvPEivToiIrXzfUXRoQMBG4bKgwK1rkNEXJnFyAcfN24cWVlZPP/886SlpREVFcWyZcuIiIgAIC0trcqZHZGRkSxbtoypU6cyZ84cwsLCeO211xg7dqyjz7Fjx+jdu7fj61deeYVXXnmFoUOHsnr1agDHFr3Dhg2rkmfBggVMnDgRNzc3duzYwcKFC8nOziY0NJQrrriCRYsW4ePjU0+vhojIhTtdauWn/eUba1ypoqNBuKZbCC8u20P8wSxyikrxa3L+I/siIs7C0HM6Gjqd0yEiF9vqvRlMXLCREF8v4p+4ssGf7RAOrAsPJzw1FY6ZIdQGtAKOGpysbsX8Xxz7jufz71t7cX2vVkbHERFxnXM6RESk7jlOIe+qU8gbkphulbtYaYqViLgmQ6dXiYhI3bHb7Y6tchvLeo43gSNvvsnxoiKiU3ZAaA+gidGx6lxM92Be/+EAq/dmcLrUipe7zl4REdeiokNEpIHYdzyf1OwiPC1mBrcPMDrORXEtwLXXVnx1i4FJ6lePVn6E+HqRnnua+INZXNFIikoRaTg0vUpEpIFYmVg+9ebSDgE08dAn4Q2JyWRy7GL1nQ4KFBEXpKJDRKSBcKzn0KfgDVLluo6Vicex2rQHjIi4Fk2vEhFpAE4WlLAl+RTQuIqOzYD75s14lJTQpflB6Noe8ACiDU5W9wa0a4mPl4XM/BISkk/Rt21LoyOJiJw3jXSIiDQAq/dmYLdD11Bfwpo3vIXUZ3M90PL66+kyeDA0nwAMrmhteNzdzI4NAnRQoIi4GhUdIiINgE4hbxxiupdPsfpuVzo6ZktEXImKDhERF1dqtfHj3hNA+fkc0nBd3ikQD4uZpKxC9mfkGx1HROS8qegQEXFxG4+cJK+4DP+mHvQKb250HKlHzTwtXNahfDvkFdrFSkRciIoOEREXt6riQMArugRhNusU8oYuplv51rla1yEirkRFh4iIi1ul9RyNylVdgzGZYPvRHI5lFxkdR0TkvKjoEBFxYYdO5HMoswB3NxOXdWwcp5A3doE+nvSNaAH8ciCkiIizU9EhIuLCKkc5BkT64+PlbnAauVgqDwpcsUtFh4i4BhUdIiIu7PtfreeQxuOainUd6w5lkVNYanAaEZHfp6JDRMRF5RSVsvHISQCu1la5jUrbgKZ0DvahzGbnh70ZRscREfldKjpERFzUj/tOUGaz0yGoGRH+TY2OY4hEwDcxkbycHGiWAuRUtDZ8Md3LRzu+09a5IuICVHSIiLio7ysWEV/ViEc5fABfHx98fH3BJwzwrWht+CrXdcTtO8HpUqvBaUREzk1Fh4iICyqz2li9r/wU8qu6BBucRowQ1cqXUD8vCkus/Hwg0+g4IiLnpKJDRMQFbUnOJruwlObe7vRp09zoOGIAk8n0y0GB2sVKRJycxegAIiJSc5VTq4Z1CsTi1ng/P5oFdJ81C9/cXAYNS4BhvSmfYjXN4GQXR0z3EN6PT2Jl4nGsNjtuOpFeRJyUig4RERf0feUp5F0b99SqWcC6WbMIT02F+8zAEqAVjaXo6B/ZEl8vC1kFJWxJPkW/ti2NjiQiUq3G+/GYiIiLSsoq4EBGPhazics7BRodRwzk7mZ2FJ4rtIuViDgxFR0iIi6m8kDAfm1b4tdEp5A3do51HbuPY7fbDU4jIlI9FR0iIi7m+z3aKld+cXmnQDwsZpKyCtl3PN/oOCIi1VLRISLiQvJOl7L+UPkp5I19PYeUa+ppYUiHAEBTrETEeanoEBFxIT/uy6TMZqddYFMiAxrnKeRypsrTyVfs1ta5IuKcVHSIiLgQxynkXTS1Sn5xdddgzCbYkZrDsewio+OIiJxBRYeIiIuw2uz8sFdb5cqZ/Jt50jeifLtcTbESEWekokNExEUkJJ/iVGEpvl4W+ka0MDqOOBlNsRIRZ6aiQ0TERVQeCDisc1CjPoX81/oAh/v0Yc/AgZAcCAysaG18rqnYOnf94ZNkF5YYnEZEpCqdSC4i4iIc6zm0Va7DEoAlS4yO4RQi/JvSJcSHPel5rNqTwU19wo2OJCLioI/KRERcQMrJ8jMY3MwmhnVS0SHVcxwUuEtTrETEuajoEBFxAZWjHH0jWuDnrVPIpXox3UMAiNt3gtOlVoPTiIj8QkWHiIgLqFzPoalVci7dw3wJ8/OiqNTKT/szjY4jIuKgokNExMnlF5fpFPKzGAOsGTOGPYMGwfoQYFBFa+NkMpkcox0rdmvrXBFxHio6RESc3Jp9Jyix2ogMaEr7wGZGx3EqW4DILVvosm4dtDkBrKtobbwq13WsTMzAarMbnEZEpJyKDhERJ1c5tepKnUIu56FfZEv8mrhzsqCEzUmnjI4jIgKo6BARcWpWm50ftJ5DasDdzcxVFQWqTicXEWehokNExIltTckmq6AEHy8L/dq2NDqOuIhfn05ut2uKlYgYT0WHiIgTi91dvlXusM5BuOsUcjlPl3cKxNNiJvlkIXuP5xkdR0RERYeIiDOLrdiB6Jpu2rVKzp+3h4UhHQMA+G6nDgoUEeOp6BARcVKHTuRz8EQB7m4mhnUONDqOuBhtnSsizkRFh4iIk6qcWjWwnT++XjqFXGrmqi5BmE2w61guR08VGh1HRBo5FR0iIk5qRUXREaOpVVIL/s086Vux+UBlASsiYhSL0QFERORMJ/KK2ZJcfsbC1So6zmoasGvaNFJycxm0NwFCewO+RsdyGjHdgtlw+CQrdh3nrksjjY4jIo2Yig4RESe0as9x7Hbo0cqPUL8mRsdxWtMApk0zOobTiukWwj+WJrLhyElOFZTQoqmH0ZFEpJHS9CoRESdUOR1Gu1bJhWjj702XEB+sNjurKg6ZFBExguFFx9y5c4mMjMTLy4vo6GjWrFlzzv5xcXFER0fj5eVFu3btePPNN6t8f9euXYwdO5a2bdtiMpmYPXt2rR7Xbrfz7LPPEhYWRpMmTRg2bBi7du26oOcqInI+CkvKWLM/E1DRIRdOu1iJiDMwtOhYtGgRU6ZM4amnniIhIYEhQ4YwcuRIkpOTq+1/+PBhRo0axZAhQ0hISODJJ5/koYceYvHixY4+hYWFtGvXjn/961+EhITU+nFfeuklZs2axeuvv87GjRsJCQnhmmuuIS9PhyyJSP1asz+T4jIb4S2a0CXEx+g4Ti0PyM3LIy83F/KOAbkVrVKpciOCuH0nKCqxGpxGRBork91utxv14AMGDKBPnz688cYbjrauXbtyww03MGPGjDP6P/bYYyxZsoTExERH2+TJk9m2bRvx8fFn9G/bti1TpkxhypQpNXpcu91OWFgYU6ZM4bHHHgOguLiY4OBgZs6cyX333Xdezy83Nxc/Pz9ycnLw9dXCRhE5P9P/t43PNh/lrkvb8vfruhsdx6mFA+vCwwlPTYVjZgi1Aa2AowYncx52u53LZv5AanYR79zZV6NnIlInavo+17CRjpKSEjZv3kxMTEyV9piYGNauXVvtfeLj48/oP3z4cDZt2kRpaWmdPe7hw4dJT0+v0sfT05OhQ4eeNZuISF0os9r4PlHrOaTumEwmx/9LK3ZpipWIGMOwoiMzMxOr1UpwcNVfqsHBwaSnV/9DMT09vdr+ZWVlZGZm1tnjVv5Zk2xQPhqSm5tb5SYiUhObk05xqrAUvybu9K84Y0HkQsV0L/99tjLxOGVWm8FpRKQxMnwhuclkqvK13W4/o+33+lfXXhePW9NsM2bMwM/Pz3Fr3bp1jTKJiFTuWnVVlyAsbob/iJYGon/blvg1cedUYSmbkk4ZHUdEGiHDfqMFBATg5uZ2xshBRkbGGSMMlUJCQqrtb7FY8Pf3r7PHrVyAXpNsAE888QQ5OTmOW0pKynllEhGB8g82YjW1SuqBxc3MVV2DAFixS6eTi8jFZ1jR4eHhQXR0NLGxsVXaY2NjGTx4cLX3GTRo0Bn9V6xYQd++fXF3d6+zx42MjCQkJKRKn5KSEuLi4s6aDcrXffj6+la5iYicr/0Z+SRlFeJhMXN5p0Cj40gDE9Ptl61zDdxDRkQaqVqdSH748GEiIyMv+MGnTZvG+PHj6du3L4MGDeLtt98mOTmZyZMnA+UjB6mpqSxcuBAo36nq9ddfZ9q0adx7773Ex8czb948Pv74Y8c1S0pK2L17t+PvqampbN26lWbNmtGhQ4fzelyTycSUKVN48cUX6dixIx07duTFF1/E29ub22+//YKft4hIdSqnVl3a3p+mnrX68SxyVpd3CsDTYuboqSIS0/LoFqYPxkTk4qnVb7UOHTpw+eWXc88993DzzTfj5eVVqwcfN24cWVlZPP/886SlpREVFcWyZcuIiIgAIC0trcrZGZGRkSxbtoypU6cyZ84cwsLCeO211xg7dqyjz7Fjx+jdu7fj61deeYVXXnmFoUOHsnr16vN6XIBHH32UoqIi7r//fk6dOsWAAQNYsWIFPj7aM19E6scKxynk1Z8xJHIhvD0sXN4pkNjdx1mxO11Fh4hcVLU6p2Pnzp3Mnz+fDz/8kOLiYsaNG8c999xD//796yOjy9I5HSJyvtJyihg0YxUmE6x/4iqCfGv3YU5jo3M6auZ/m1J45LPtdAnx4dsplxsdR0Rc2EU5pyMqKopZs2aRmprKggULSE9P57LLLqN79+7MmjWLEydO1OayIiKN1nc7yzeuiG7TQgWH1JuruwbjZjaxJz2PQyfyjY4jIo3IBS0kt1gs3HjjjXz66afMnDmTgwcPMn36dMLDw7nzzjtJS0urq5wiIg3atxWHto2I0tSqmvgKOPnVV+xZuxay3wfWVrRKdVo09WBw+/LdHpft0O9oEbl4Lqjo2LRpE/fffz+hoaHMmjWL6dOnc/DgQVatWkVqairXX399XeUUEWmwsvKL2XD4JADDu6voqIlo4JLoaLoMGgRd7wAGVbTK2YzuEQrA0h06nVxELp5aFR2zZs2iR48eDB48mGPHjrFw4UKSkpL4xz/+QWRkJJdeeilvvfUWW7Zsqeu8IiINTuzu49jsENXKl9YtvY2OIw1cTPcQ3MwmEtNyOZxZYHQcEWkkalV0vPHGG9x+++0kJyfz5Zdfcu2112I2V71UmzZtmDdvXp2EFBFpyBxTqzTKIRdBS02xEhED1GrL3NjYWNq0aXNGoWG320lJSaFNmzZ4eHgwYcKEOgkpItJQ5Z4u5ecDmYDWc9TGN0Dzb76hSVER0RE7oH8PoAlwrcHJnNuoHqGs2Z/Jsh1pPHBFB6PjiEgjUKuRjvbt25OZmXlG+8mTJ+vk0EARkcbihz0ZlFrtdAhqRocgnQNUU5OBtpMnE/2HP0DrfwJ/qGiVcxleMcVq17FckrI0xUpE6l+tio6zHe2Rn59f64MCRUQao+U7NLVKLr6WTT0Y1K58itVSTbESkYugRtOrpk2bBoDJZOKZZ57B2/uXBY9Wq5X169fTq1evOg0oItJQFZVYWb0vA9DUKrn4RvUI5acD5VOs7h+mKVYiUr9qVHQkJCQA5SMdO3bswMPDw/E9Dw8PevbsyfTp0+s2oYhIAxW37wSnS22Et2hC97DfP81VpC4N7x7M377cwc7UXJKzCmnjr53TRKT+1Kjo+OGHHwC46667+Pe//31eR56LiEj1vvvVrlUmk8ngNNLY+DfzZGA7f9YezGLpjjT+PKy90ZFEpAGr1ZqOBQsWqOAQEbkAJWU2ViYeBzS1SowzquKgQG2dKyL17bxHOm666Sbee+89fH19uemmm87Z9/PPP7/gYCIiDdnag5nknS4j0MeTPm1aGB1HGqkRUSE889VOdqTmaIqViNSr8y46/Pz8HMP/fn5+9RZIRKQxqJxaFdMtGLNZU6vEGAHNPBkQ6U/8oSyW7Uxj8lBNsRKR+nHeRceCBQuq/buIiNRMmdXGil3lU6tGRoUanEYau1GXhJYXHTtUdIhI/anVmo6ioiIKCwsdXyclJTF79mxWrFhRZ8FERBqqDYdPklVQQnNvdwa0a2l0HJfWDChs1ox8Hx8osgA+Fa1yvkZ0D8Fsgu1Hc0g5Wfj7dxARqYVaFR3XX389CxcuBCA7O5v+/fvz6quvcv311/PGG2/UaUARkYbmm4pFuyO6h+DuVqsfw1JhD9Bpzx6a5eZCu2Igt6JVzlegjyf9I8uL3+U7taBcROpHrX7bbdmyhSFDhgDw2WefERISQlJSEgsXLuS1116r04AiIg1JmdXGtzvL13OMvkRTq8Q5jK7YxWrpjnSDk4hIQ1WroqOwsBAfHx8AVqxYwU033YTZbGbgwIEkJSXVaUARkYZk3aGTnCwooYW3O4Pa+RsdRwSA4VEhmEywLSVbU6xEpF7Uqujo0KEDX375JSkpKXz33XfExMQAkJGRofM7RETOYemOYwCMiArFoqlV4iSCfLwYGFleBH+zXVOsRKTu1eo33jPPPMP06dNp27YtAwYMYNCgQUD5qEfv3r3rNKCISENRarWxvGJq1XWaWlUnHgG+feQR1k+aBKv7AZMqWqWmrusZBsCSbccMTiIiDZHJbrfba3PH9PR00tLS6NmzJ2Zzee2yYcMGfH196dKlS52GdFW5ubn4+fmRk5OjESARIW7fCSbM30BAMw/WPXGVRjrqQDiwLjyc8NRUOGaGUBvQCjhqcDLXc6qghH7/XEmZzc7KaZfTIcjH6Egi4sRq+j631r/xQkJC6N27t6PgAOjfv78KDhGRs1i6vXJqVYgKDnE6LZp6MKRjAABLtmmKlYjUrVr91isoKODpp59m8ODBdOjQgXbt2lW5iYhIVSVlNr6rOBBwdI8wg9OIVG9Mr/L/N7/ZdoxaToQQEanWeZ9I/muTJk0iLi6O8ePHExoaislkqutcIiINys8HM8kpKiWg2S9nIog4m2u6heBp2cGhzAJ2HcslqpWf0ZFEpIGoVdGxfPlyli5dyqWXXlrXeUREGqSlFTsCjeoRgptZH9SIc2rmaeGqrkEs25HOkm3HVHSISJ2p1fSqFi1a0LKlPqkTETkf5VOrKg4E7KFdq8S5jen5yxQrm01TrESkbtSq6HjhhRd45plnKCzUAUIiIr/npwMnyDtdRpCPJ33b6gMbcW7DOgfRzNPCsZzTbE4+ZXQcEWkgajW96tVXX+XgwYMEBwfTtm1b3N3dq3x/y5YtdRJORKQh+MYxtSpUU6vE6Xm5uxHTPZjPt6Ty9bZj9FOhLCJ1oFZFxw033FDHMUREGqbiMiuxlbtW6UBAcRHX9Qzj8y2pLNuRxjPXdtMWzyJywWpVdPz973+v6xwiIg3SD3tOkFdcRqifF9FtWhgdp8EZDSSOHs3xkyeJ3r8TQqMAfTJ/oS7rEEALb3cy80uIP5TFkI6BRkcSERdXq6IDIDs7m88++4yDBw/yyCOP0LJlS7Zs2UJwcDCtWrWqy4wiIi7rq62pQPniXLOmVtW5twDeesvoGA2Ou5uZUT1C+XB9Mku2HlPRISIXrFbjpdu3b6dTp07MnDmTV155hezsbAC++OILnnjiibrMJyLisnJPl/L9ngzgl0PXRFzFdRW7WH27K53iMqvBaUTE1dWq6Jg2bRoTJ05k//79eHl5OdpHjhzJjz/+WGfhRERc2bc70ykps9ExqBndQn2NjiNSI/3btiTY15O802XE7T1hdBwRcXG1Kjo2btzIfffdd0Z7q1atSE9Pv+BQIiINwZKtxwC4vlcYJpOmVolrMZtNXHtJ+WjHkm3HDE4jIq6uVkWHl5cXubm5Z7Tv3buXwEDN+xQRycg9zdqDmQBc30vr3OpLX2Bb374cDw+H3U2B8IpWqQuVBwWuTDxOfnGZwWlExJXVqui4/vrref755yktLQXAZDKRnJzM448/ztixY+s0oIiIK/p6exo2O/Rp05zWLb2NjtNgpQP+6ekEp6ZCi9NAakWr1IVLwv1oF9CU06U2vt2p11VEaq9WRccrr7zCiRMnCAoKoqioiKFDh9KhQwd8fHz45z//WdcZRURcTuWuVTf01iiHuC6TycSNFf8Pf5Fw1OA0IuLKarVlrq+vLz/99BM//PADmzdvxmaz0adPH66++uq6zici4nIOnchn+9Ec3MwmRvXQgYDi2m7o3YpXY/ex9mAWaTlFhPo1MTqSiLigGhcdNpuN9957j88//5wjR45gMpmIjIwkJCQEu92uxZIi0uh9VbGAfEjHAAKaeRqcRuTCtG7pTb+2Ldh45BRLth7jvqHtjY4kIi6oRtOr7HY7Y8aMYdKkSaSmptKjRw+6d+9OUlISEydO5MYbb6yvnCIiLsFutzt2+rleZ3NIA3Fj73AAvkhINTiJiLiqGhUd7733Hj/++CPff/89CQkJfPzxx3zyySds27aNlStXsmrVKhYuXFhfWUVEnN72ozkczizAy91MTLcQo+OI1InRPULxcDOzJz2PxLQzd68UEfk9NSo6Pv74Y5588kmuuOKKM7535ZVX8vjjj/Phhx/WWTgREVdT+UnwNd1CaOpZq2VzIk7Hz9udK7sEARrtEJHaqVHRsX37dkaMGHHW748cOZJt27ZdcCgREVdUUmZzTK26qY92rZKG5caK/6e/2pqK1WY3OI2IuJoaFR0nT54kODj4rN8PDg7m1KlTFxxKRMQVrd6bwcmCEgJ9PBnSIcDoOCJ16orOQTT3dud4bjHxB7OMjiMiLqZGY/9WqxWL5ex3cXNzo6xMJ5aKSOP02ebycwxu7N0Ki1utjkGSGnoJ2P/SS6QWFjLgUAKE9gZ0GGN98LCYGd0jlA/XJ/N5wlEu66jCWkTOX42KDrvdzsSJE/H0rH4LyOLi4joJJSLiarLyi1m1JwOAsX3CDU7TeNwOcPvtRsdoNG7q04oP1yfz3c50Cm8ow9tD65ZE5PzU6KfFhAkTfrfPnXfeWeswIiKuasm2Y5TZ7PRo5UfnEB+j44jUiz5tWtCmpTfJJwuJ3X2c63tp7ZKInJ8ajf8vWLDgvG41MXfuXCIjI/Hy8iI6Opo1a9acs39cXBzR0dF4eXnRrl073nzzzTP6LF68mG7duuHp6Um3bt344osvqny/bdu2mEymM24PPPCAo8/EiRPP+P7AgQNr9NxEpPFYvKV8atXN0RrlkIbLZDJxQ+/yQuPzLdrFSkTOn6GTjhctWsSUKVN46qmnSEhIYMiQIYwcOZLk5ORq+x8+fJhRo0YxZMgQEhISePLJJ3nooYdYvHixo098fDzjxo1j/PjxbNu2jfHjx/OHP/yB9evXO/ps3LiRtLQ0xy02NhaAW265pcrjjRgxokq/ZcuW1cOrICKubk96LjtTc3F3MzGmpw4EvJj2Avv37uXwrl1waDmwq6JV6stNFUXHmv0nOJ572uA0IuIqTHa73bB97wYMGECfPn144403HG1du3blhhtuYMaMGWf0f+yxx1iyZAmJiYmOtsmTJ7Nt2zbi4+MBGDduHLm5uSxfvtzRZ8SIEbRo0YKPP/642hxTpkzhm2++Yf/+/ZhMJqB8pCM7O5svv/yy1s8vNzcXPz8/cnJy8PX1rfV1RMS5/XPpbt5Zc5jh3YN5a3xfo+M0KuHAuvBwwlNT4ZgZQm1AK+CowckatlveXMvGI6d4dERn7h/Wweg4ImKAmr7PNWyko6SkhM2bNxMTE1OlPSYmhrVr11Z7n/j4+DP6Dx8+nE2bNlFaWnrOPme7ZklJCR988AF33323o+CotHr1aoKCgujUqRP33nsvGRkZNXqOItLwlVltfJFQfjbHzdGtDU4jcnHcUvH/+mebjmLgZ5ci4kIMKzoyMzOxWq1nnPsRHBxMenp6tfdJT0+vtn9ZWRmZmZnn7HO2a3755ZdkZ2czceLEKu0jR47kww8/ZNWqVbz66qts3LiRK6+88pw7dBUXF5Obm1vlJiIN24/7T5CZX4x/Uw+GdQ40Oo7IRTHqklC8Pdw4lFnA5iSdzyUiv8/wjeR/O7pgt9vPaPu9/r9tr8k1582bx8iRIwkLqzoPe9y4cYwePZqoqCiuu+46li9fzr59+1i6dOlZs82YMQM/Pz/HrXVrfeop0tAt3ly+mHZMrzDcdTaHNBLNPC2M6hEKwP82aSqbiPw+w35DBgQE4ObmdsYIREZGxllPPQ8JCam2v8Viwd/f/5x9qrtmUlISK1euZNKkSb+bNzQ0lIiICPbv33/WPk888QQ5OTmOW0pKyu9eV0Rc18mCEmJ3Hwd0Noc0Pn/oW/7B2jfbj1FYooOBReTcDCs6PDw8iI6OduwcVSk2NpbBgwdXe59Bgwad0X/FihX07dsXd3f3c/ap7poLFiwgKCiI0aNH/27erKwsUlJSCA0NPWsfT09PfH19q9xEpOH6fMtRSqw2olr5EtXKz+g4IhdVv7YtaOvvTUGJlWU7qp/CLCJSydC5ANOmTePdd99l/vz5JCYmMnXqVJKTk5k8eTJQPnLw68MGJ0+eTFJSEtOmTSMxMZH58+czb948pk+f7ujz8MMPs2LFCmbOnMmePXuYOXMmK1euZMqUKVUe22azsWDBAiZMmIDFUvWMxPz8fKZPn058fDxHjhxh9erVXHfddQQEBHDjjTfW3wsiIi7Dbrfzycby0cxb+7UxOI3IxWcymRzn0ny6SSP7InJuNTqRvK6NGzeOrKwsnn/+edLS0oiKimLZsmVEREQAkJaWVuXMjsjISJYtW8bUqVOZM2cOYWFhvPbaa4wdO9bRZ/DgwXzyySf87W9/4+mnn6Z9+/YsWrSIAQMGVHnslStXkpyczN13331GLjc3N3bs2MHChQvJzs4mNDSUK664gkWLFuHjo5OGRQQ2J53iQEY+TdzduL6XzuaQxmlsdDivxu5jw+GTJGUVEOHf1OhIIuKkDD2no6HTOR0iDddfP93G4i1HuSU6nJdv6Wl0nEZL53QY7875G/hx3wn+cmUH/hrT2eg4InKRuMw5HSIiriqnqJSlO8rP5ri1v6ZWSeP2h77lU6w+23wUq02fY4pI9VR0iIjU0FdbUzldaqNTcDP6tGludJxGbSNg3riR4ykpYN4MpFS0ysVydddg/Jq4k5Zzmp8PZBodR0SclIoOEZEasNvtfLzhlwXk5zpXSOpfKBAWGkpweDgE96J8wtXZdxmUuuf1q3VNWlAuImejokNEpAa2H80hMS0XD4uZm/q0MjqOiFOoPLNjxa7jnCooMTiNiDgjFR0iIjXwycbyHfVGRoXQ3NvD4DQizqF7mC/dw3wpsdpYvEWL+EXkTCo6RETOU0FxGUu2Viwg19kcTuFtIPbtt4mfNQt+vAOYVdEqF5PJZOL2AeX/Jj7akIw2xhSR31LRISJynpZsO0ZBiZXIgKYMbNfS6DgCPA90ff55Bv31r9DxY+CvFa1ysY3pGYa3hxuHThSw/vBJo+OIiJNR0SEich7sdjsL45MAuK1/ay0gF/kNHy93x4Lyjzck/05vEWlsVHSIiJyHzUmnSEzLxdNidiyaFZGqbu8fAcDyHemc1IJyEfkVFR0iIuehcpRjTM8wLSAXOYse4X5EtSpfUP65FpSLyK+o6BAR+R0n8opZvjMNgDsHtTU2jIiTqxzt0IJyEfk1FR0iIr/jkw3JlFrt9GrdnB7hfkbHEXFqY3qF0bRiQfm6Q1pQLiLlVHSIiJxDmdXGRxWLYu8cFGFwGhHn18zTwphe5QdnakG5iFRS0SEicg4rE4+TlnOalk09GNUj1Og4Ii7hjxVndny7UwvKRaScig4RkXP477ryBeTj+rXGy93N4DQiriGqlR89WvlRYrXx6aYUo+OIiBNQ0SEichYHMvL4+UAWZtMvn9yKc+kEpHbqxJFu3SDdF+hW0SpGGz+wfDriB+uSsNq0oFyksbMYHUBExFnN++kIAFd3DSa8hbexYaRaqwBWrTI6hlRjTK8wXlyeyNFTRazak8E13YKNjiQiBtJIh4hINU4WlDjOGbjnskiD04i4Hi93N8b1Kz9I8/21R4wNIyKGU9EhIlKNj9YnUVxmo0crP/pHtjQ6johLumNABGYT/HQgkwMZeUbHEREDqegQEfmN4jIr71ecQH7PZZGYTCaDE4m4ptYtvbmqa/m0qoUV/6ZEpHFS0SEi8hvfbEvjRF4xwb6e2ibXyf0RWPXHP7J9+HD4uS0wvKJVnMWEQW0BWLz5KHmnS40NIyKGUdEhIvIrdrudeT8dBmDC4LZ4WPRj0pnFAZ3i4rhkxQpolwKsqGgVZ3FpB3/aBzaloMTK4s1HjY4jIgbRb1MRkV+JP5TF7rRcmri7cXt/bZMrcqFMJhMTBrcFyqdY2bR9rkijpKJDRORX5leMcoyNbkVzbw+D04g0DDf1CaeZp4VDmQX8dCDT6DgiYgAVHSIiFQ5k5PP9ngwA7rpU2+SK1JVmnhZujg4HtH2uSGOlokNEpMJbcQex2yGmWzDtA5sZHUekQblzUPkJ5av2ZnDoRL7BaUTkYlPRISICHMsu4sutqQBMHtbe4DQiDU+7wGZc3TUIux3HZg0i0nio6BARofxNUKnVzsB2LenTpoXRcUQapElD2gHw2eajnCwoMTiNiFxMKjpEpNHLLizh4w3JAPx5WAeD04g0XAMiW9KjlR/FZTY+WKfDAkUaExUdItLoLYxPorDESrdQXy7vGGB0HJEGy2QyMWlI+SYNC+OPcLrUanAiEblYVHSISKNWWFLGgp/L55f/eVh7TCaTwYmkJu4Fdt57L/FTp8Ley4GpFa3irEb1CCXMz4vM/BK+TEg1Oo6IXCQWowOIiBjp040pnCosJcLfm5FRIUbHkRr6O8Df/250DKkBdzczd10ayT+XJfLuT4f5Q9/WmM0q9kUaOo10iEijVVxm5e0fDwFw75B2WNz0I1HkYhjXvzXNPC0cyMgnbt8Jo+OIyEWg37Ai0mh9tvkox3JOE+zr6Ti4TETqn6+XO7f2aw3AO2sOGZxGRC4GFR0i0iiVlNmY+8NBAP48tD1e7m4GJxJpXO66LBI3s4m1B7PYmZpjdBwRqWcqOkSkUfps81FSs4sI8vHk1v5tjI4jtRQOHA0PB5MJ0twAU0WrOLtWzZtw7SWhALyx+qDBaUSkvqnoEJFGp6TMxpwfDgAwWaMcIob587D2ACzbmcbBE/kGpxGR+qSiQ0QancVbykc5An08uX2ARjlEjNIlxJeruwZjt8ObGu0QadBUdIhIo6JRDhHncv8V5aMdXySkkppdZHAaEakvKjpEpFH5fMtRjp4qIqCZJ3/UKIeI4fq0acHg9v6U2ey8HafRDpGGSkWHiDQaxWVW/rOqcpSjnUY5RJzEA1d0AOCTjSmcyCs2OI2I1AcVHSLSaHy4LpnU7CJCfL24Y2CE0XFEpMLg9v70bN2c4jIb838+bHQcEakHKjpEpFHILy5zrOV46KqOGuUQcSImk4kHKnay+m98EjmFpQYnEpG6pqJDRBqF+T8dJqughLb+3tzSV+c4iDibq7sG0yXEh/ziMt79SaeUizQ0KjpEpME7VVDCOz+Wv4n5a0xn3N30o0/E2ZjNJh6+qiMAC34+wqmCEoMTiUhd0m9eEWnw3og7SF5xGd1CfRndI9ToOFKHPgCOffAB2779Fo6/Cnxb0SquaHj3ELqG+pJfXMY7azTaIdKQWIwOICJSn9JzTvP+2iMAPDKiM2azydhAUqeGAQwbVvHVcMNySN0wm01Mvbojf/rvZt5be4RJQ9rRsqmH0bFEpA5opENEGrRZsXspLrPRv21LhnUKNDqOiPyOa7oFE9XKl8ISK2/9qHM7RBoKFR0i0mDtOpbD/zYfBeDxUV0wmTTKIeLsTCYTU6/uBMDCtUlk5uvcDpGGwPCiY+7cuURGRuLl5UV0dDRr1qw5Z/+4uDiio6Px8vKiXbt2vPnmm2f0Wbx4Md26dcPT05Nu3brxxRdfVPn+s88+i8lkqnILCQmp0sdut/Pss88SFhZGkyZNGDZsGLt27brwJywiF4XdbufFZYnY7XDtJaH0adPC6EhSD1YDG1avZtt338HW2cB3Fa3iyq7sEkTPcD+KSq28pVPKRRoEQ4uORYsWMWXKFJ566ikSEhIYMmQII0eOJDk5udr+hw8fZtSoUQwZMoSEhASefPJJHnroIRYvXuzoEx8fz7hx4xg/fjzbtm1j/Pjx/OEPf2D9+vVVrtW9e3fS0tIctx07dlT5/ksvvcSsWbN4/fXX2bhxIyEhIVxzzTXk5eXV/QshInXuh70Z/HwgCw+LmcdGdDE6jtSTO4CwO+6g54gREPxXYERFq7gyk8nElGsqRjvik0jLKTI4kYhcKJPdbrcb9eADBgygT58+vPHGG462rl27csMNNzBjxowz+j/22GMsWbKExMRER9vkyZPZtm0b8fHxAIwbN47c3FyWL1/u6DNixAhatGjBxx9/DJSPdHz55Zds3bq12lx2u52wsDCmTJnCY489BkBxcTHBwcHMnDmT++6777yeX25uLn5+fuTk5ODr63te9xGRC1dqtTFi9o8cPFHAfUPb8cTIrkZHknoSDqwLDyc8NRWOmSHUBrQCjhqcTC6U3W7nD2/Fs/HIKW7t15p/jb3E6Egi8is1fZ9r2EhHSUkJmzdvJiYmpkp7TEwMa9eurfY+8fHxZ/QfPnw4mzZtorS09Jx9fnvN/fv3ExYWRmRkJLfeeiuHDv2yNd/hw4dJT0+vch1PT0+GDh161mxQXpjk5uZWuYnIxffJhmQOniigZVMPHriig9FxRKQWTCYTj48sH6X8dFMKBzI000DElRlWdGRmZmK1WgkODq7SHhwcTHp6erX3SU9Pr7Z/WVkZmZmZ5+zz62sOGDCAhQsX8t133/HOO++Qnp7O4MGDycrKclyj8n7nmw1gxowZ+Pn5OW6tW7c+10sgIvUg93Qp/7dyPwBTru6Ir5e7wYlEpLaiI1pyTbdgbHZ46du9RscRkQtg+ELy3+4mY7fbz7nDTHX9f9v+e9ccOXIkY8eOpUePHlx99dUsXboUgPfff/+Csj3xxBPk5OQ4bikpKWftKyL1Y3bsfk4WlNA+sCm39W9jdBwRuUCPDu+M2QQrdh9nc9Ipo+OISC0ZVnQEBATg5uZ2xshBRkbGGSMMlUJCQqrtb7FY8Pf3P2efs10ToGnTpvTo0YP9+/c7rgHU+Dqenp74+vpWuYnIxbMnPZf3448A8PfruuPuZvjnKiJygToG+3BLdPnMgZnL92DgUlQRuQCG/Ub28PAgOjqa2NjYKu2xsbEMHjy42vsMGjTojP4rVqygb9++uLu7n7PP2a4J5WsxEhMTCQ0NBSAyMpKQkJAq1ykpKSEuLu6c1xER49jtdv7+1S6sNjsjuodwuQ4CFGkwplzTEU+LmQ1HTrJqT4bRcUSkFgz9GHDatGm8++67zJ8/n8TERKZOnUpycjKTJ08Gyqcr3XnnnY7+kydPJikpiWnTppGYmMj8+fOZN28e06dPd/R5+OGHWbFiBTNnzmTPnj3MnDmTlStXMmXKFEef6dOnExcXx+HDh1m/fj0333wzubm5TJgwAajYqm/KFF588UW++OILdu7cycSJE/H29ub222+/OC+OiNTI19vTWH/4JJ4WM3+7VrtViTQkoX5NmHhpWwBmLN9DqdVmbCARqTGLkQ8+btw4srKyeP7550lLSyMqKoply5YREREBQFpaWpUzOyIjI1m2bBlTp05lzpw5hIWF8dprrzF27FhHn8GDB/PJJ5/wt7/9jaeffpr27duzaNEiBgwY4Ohz9OhRbrvtNjIzMwkMDGTgwIGsW7fO8bgAjz76KEVFRdx///2cOnWKAQMGsGLFCnx8fC7CKyMiNZFfXMY/l+4G4IErOhDewtvgRCJS1+4f1oFPN6ZwICOfj9YnM2FwW6MjiUgNGHpOR0OnczpELo4ZyxN5K+4QbVp6s2Lq5Xi5uxkdSS4SndPRuPx3XRJPf7mT5t7urJ4+jObeHkZHEmm0XOacDhGRunAgI595aw4D8PfruqngaGSOAuFHj4LdDqFWwI4Kjobrtn6t6RzsQ3ZhKbMrtsYWEdegokNEXJbdbueZr3ZSZrNzZZcgrup69t3lRMT1WdzMPHNdN6B81EMHBoq4DhUdIuKyFm9JZe3BLDwtZv5e8UZERBq2SzsEcHXXYKw2Oy98k2h0HBE5Tyo6RMQlZeUX84+KxeNTru5EhH9TgxOJyMXy1OiuuLuZiNt3gh+0ha6IS1DRISIu6R9LE8kuLKVrqC+ThkQaHUcM8hzw7XPPET9tGqy+AphW0SoNWWRAU+66tPzf/bNf7+J0qdXgRCLye1R0iIjLidt3gi8SUjGb4F839dDJ443YO0DUO+8w6P/+Dzr/CPxfRas0dA9d1ZFgX0+Ssgp5Y/VBo+OIyO/Qb2oRcSmFJWU89cUOACYOjqRn6+bGBhIRQzTztPDMtd0BeCPuIIczCwxOJCLnoqJDRFzKv1fu5+ipIlo1b8JfYzoZHUdEDDSqRwhDOgZQUmbj70t2oaPHRJyXig4RcRnbj2bz7k/lZ3K8cEN3mnpaDE4kIkYymUy8cH0UHhYzP+47wbId6UZHEpGzUNEhIi6huMzKXz/dhtVmZ0zPMK7sojM5RATaBjTlz0PbA/D8N7vIO11qcCIRqY6KDhFxCbNX7md/Rj4BzTx5bkx3o+OIiBP587D2RPh7czy3mJe/22t0HBGphooOEXF6CcmneCuufHeaF2+MokVTD4MTiYgz8XJ348UbewCwMD6JDYdPGpxIRH5LRYeIOLXTpVam/28bNjvc2LsVMd1DjI4kIk7o0g4BjOvbGoDHF2/X2R0iTkZFh4g4tVmx+zh4ooAgH0/+fl03o+OIiBN7cnRXgnw8OZRZwL+/3290HBH5FRUdIuK0Nied5J01hwCYcVMPmntrWpVUNRTYN3Qo22Ni4FBrIKaiVRojvybu/OOGKADe/vEQO1NzDE4kIpW036SIOKW806VMWbQVux3G9gnnqq7arUrO9CHAhx8aHUOcSEz3EEZfEsrS7Wk88tl2vnrgUjws+oxVxGj6VygiTunZJbtJOVl+CODfx2halYicv+fGdKeFtzuJabn8Z5WmWYk4AxUdIuJ0vtl+jMVbjmI2wexbe+Hr5W50JBFxIQHNPPlnxW5Wc344wOakUwYnEhEVHSLiVI5lF/Hk5zsAeOCKDvRr29LgRCLiikb1COWm3q2w2WHap1spKC4zOpJIo6aiQ0SchtVmZ+qireSeLqNn6+Y8dFVHoyOJk7sSWH/llRzp3h0SWgDdK1pF4Nnru9OqeROSsgr5x9JEo+OINGoqOkTEabz94yHWHz6Jt4cb/x7XC3c3/YiSc9sHtNq3j7a7d0NILrC7olUEfL3ceeWWnphM8PGGZL5PPG50JJFGS7/RRcQp7Diaw6zYvQA8e1132gY0NTiRiDQEg9r7M+mySAAeW7ydrPxigxOJNE4qOkTEcHmnS/nLx1sotdoZGRXCLX3DjY4kIg3IX2M60znYh8z8Eh75bDs2m93oSCKNjooOETGU3W7nic93cCSrkFbNmzDjph6YTCajY4lIA+Ll7sbsW3vhYTGzak8G8346bHQkkUZHRYeIGOqjDcl8sz0Ni9nEa7f11qnjIlIvuob68vfrys/8mfntHrYkaxtdkYtJRYeIGGb3sVye+3o3AI+O6Ex0RAuDE4lIQ3Z7/zZce0koZTY7f/kogZzCUqMjiTQaKjpExBD5xWU8+NEWSspsXNkliEmXtTM6kog0cCaTiRk39SDC35vU7CKmf7YNu13rO0QuBhUdInLR2e12nvpiB4cyCwj18+LVW3piNmsdh4jUPx8vd+bc3gcPNzOxu4+z4OcjRkcSaRRUdIjIRbdoYwpfbT2Gm9nEf27rTYumWschIhdPVCs/nhrdFYAZyxPZnHTS4EQiDZ/F6AAi0rgkpuXy9yW7AJge05m+bVsanEhc2TNA4jPPkJKfz6D9WyC0D9DM6FjiAu4cFMGGIydZuj2NyR9sYelfLiPI18voWCINlsmuyYz1Jjc3Fz8/P3JycvD19TU6jojhcopKGfP6TyRlFTKscyDzJ/TTtCoRMUxBcRk3zV3L3uN5REe04ON7B+Jh0SQQkfNR0/e5+pclIheFzWZn2qKtJGUVEt6iCf/3h14qOETEUE09Lbw1PhofLwubk07xwje7jY4k0mCp6BCRi+I/qw7w/Z4MPC1m3rwjWus4RMQptA1oyr9v7YXJBP9dl8Snm1KMjiTSIKnoEJF698PeDGZ/vw+Af9wQRVQrP4MTSUORBhxLS+P40aNwfCtwtKJV5Pxd2SWYKVd1AuBvX+5ka0q2sYFEGiAVHSJSr5KzCpnyyVbsdvjjgDbc0re10ZGkAekH2Pr1I7h1a7BFA60rWkVq5i9XduDqrsGUlNm4d+EmjmUXGR1JpEFR0SEi9aaoxMrkDzaTU1RKr9bNeea6bkZHEhGpltls4v/G9aRzsA8n8oq55/1NFBSXGR1LpMFQ0SEi9cJut/PUlzvYnZaLf1MP3rijD54WN6NjiYiclY+XO/Mm9iWgmQeJabk8/MlWrDZt8ilSF1R0iEi9+GBdEp9vScVsgv/c3ptQvyZGRxIR+V3hLbx5+86+eFjMrEw8zsxv9xgdSaRBUNEhInUu/mAWz31dvvXk4yO7MLh9gMGJRETOX582LXjllp4AvP3jIT7ZkGxwIhHXp6JDROpUyslC7v9wM2U2O2N6hnHvkHZGRxIRqbExPcOYcnVHoHxHq58PZBqcSMS1qegQkTpTUFzGvQs3caqwlB6t/Hjp5kswmXQAoIi4poev6siYnmGU2ezc99/N7D6Wa3QkEZelokNE6oTNZmfap1vZk55HQDNP3r4zGi93LRwXEddlMpl46eZL6B/ZkvziMiYu2EDKyUKjY4m4JBUdIlIn/v39fr7bdRwPNzNvjY/WwnERaRC83N14586+dA72ISOvmAkLNnCqoMToWCIuR0WHiFyw5TvS+Pf3+wH4x41RREe0MDiRiEjd8Wviznt39yPUz4tDJwq45/2NFJVYjY4l4lJUdIjIBdl9LJdpn24D4O5LI/mDThyXi+h7oOj77zm8cycUfQPsrGgVqVuhfk14/+7++HpZ2JKczV8+TqDMajM6lojLUNEhIrWWlV/MvQs3UVRqZUjHAJ4c1cXoSNLIdAY6du5MZPfu0G4k0L2iVaTudQr2Yd7Efo4zPJ7+ahd2uw4PFDkfKjpEpFaKy6xM/mAzqdlFtPX35j+39cbiph8pItKw9Wvbktdu7YXJBB9vSOaVFXuNjiTiEvQOQURqzG638/jiHWw8cgofTwvvTuhLc28Po2OJiFwUI6JC+ccNUQDM+eEgb6w+aHAiEedneNExd+5cIiMj8fLyIjo6mjVr1pyzf1xcHNHR0Xh5edGuXTvefPPNM/osXryYbt264enpSbdu3fjiiy+qfH/GjBn069cPHx8fgoKCuOGGG9i7t+onFRMnTsRkMlW5DRw48MKfsEgD8J9VB/giIRU3s4m5d/ShQ5CP0ZGkkfoI+OGjj1j/7rvw8wPAuxWtIvXrjwMieHxk+ZTSmd/u4b/xR4wNJOLkDC06Fi1axJQpU3jqqadISEhgyJAhjBw5kuTk5Gr7Hz58mFGjRjFkyBASEhJ48skneeihh1i8eLGjT3x8POPGjWP8+PFs27aN8ePH84c//IH169c7+sTFxfHAAw+wbt06YmNjKSsrIyYmhoKCgiqPN2LECNLS0hy3ZcuW1c8LIeJClmw7xqzYfQC8cH0UQzoGGpxIGrNHgY6PPsqAe++Fdm8C91a0itS/yUPb8+AVHQB4+qtdfL7lqMGJRJyXyW7gCqgBAwbQp08f3njjDUdb165dueGGG5gxY8YZ/R977DGWLFlCYmKio23y5Mls27aN+Ph4AMaNG0dubi7Lly939BkxYgQtWrTg448/rjbHiRMnCAoKIi4ujssvvxwoH+nIzs7myy+/rPXzy83Nxc/Pj5ycHHx9fWt9HRFnsTnpFLe9s46SMhv3DonkqdHdjI4kjVw4sC48nPDUVDhmhlAb0ArQmz+5OOx2O899vZv31h7BzWxizu19GBEVYnQskXpX0/e5ho10lJSUsHnzZmJiYqq0x8TEsHbt2mrvEx8ff0b/4cOHs2nTJkpLS8/Z52zXBMjJyQGgZcuWVdpXr15NUFAQnTp14t577yUjI+Ocz6m4uJjc3NwqN5GGIuVkIX9auImSMhvXdAvm8ZFdjY4kImI4k8nEM9d2Y2yfcKw2Ow99nMCa/SeMjiXidAwrOjIzM7FarQQHB1dpDw4OJj09vdr7pKenV9u/rKyMzMzMc/Y52zXtdjvTpk3jsssuIyoqytE+cuRIPvzwQ1atWsWrr77Kxo0bufLKKykuLj7rc5oxYwZ+fn6OW+vWOq9AGoacolLuem8jWQUldA/z5d+39sLNbDI6loiIUzCbTcwc24ORUSGUWG38aeFmNh45aXQsEadi+EJyk6nqGxe73X5G2+/1/217Ta754IMPsn379jOmXo0bN47Ro0cTFRXFddddx/Lly9m3bx9Lly49a7YnnniCnJwcxy0lJeWsfUVcRanVxoMfbeFARj7Bvp7Mm9APbw+L0bFERJyKxc3M7Ft7cXmnQIpKrUycv4HNSaeMjiXiNAwrOgICAnBzcztjBCIjI+OMkYpKISEh1fa3WCz4+/ufs0911/zLX/7CkiVL+OGHHwgPDz9n3tDQUCIiIti/f/9Z+3h6euLr61vlJuLK7HY7z3y1kzX7M2ni7sa8Cf0I8fMyOpaIiFPytLjx1h3RDGrnT0GJlQnzN5CQrMJDBAwsOjw8PIiOjiY2NrZKe2xsLIMHD672PoMGDTqj/4oVK+jbty/u7u7n7PPra9rtdh588EE+//xzVq1aRWRk5O/mzcrKIiUlhdDQ0PN6fiINwX9WHeDjDSmYTfDabb2JauVndCQREafWxMONeRP7MiCyJfnFZdw5bwPbUrKNjiViOEOnV02bNo13332X+fPnk5iYyNSpU0lOTmby5MlA+XSlO++809F/8uTJJCUlMW3aNBITE5k/fz7z5s1j+vTpjj4PP/wwK1asYObMmezZs4eZM2eycuVKpkyZ4ujzwAMP8MEHH/DRRx/h4+NDeno66enpFBUVAZCfn8/06dOJj4/nyJEjrF69muuuu46AgABuvPHGi/PiiBjs000pjq1xnxvTnWu6VT8CKSIiVXl7WJg/sR/927Ykr7iM8fPWs+NojtGxRAxlaNExbtw4Zs+ezfPPP0+vXr348ccfWbZsGREREQCkpaVVObMjMjKSZcuWsXr1anr16sULL7zAa6+9xtixYx19Bg8ezCeffMKCBQu45JJLeO+991i0aBEDBgxw9HnjjTfIyclh2LBhhIaGOm6LFi0CwM3NjR07dnD99dfTqVMnJkyYQKdOnYiPj8fHR4egScO3em8GT3y+A4A/D2vP+EFtjQ0kIuJimnpaWHBXP/pGtCD3dBl3zFvPzlQVHtJ4GXpOR0OnczrEFe04msO4t+MpLLFyY+9WzPpDz3Nu7iBipL7AvL59CUlPJ3jFKejWAggBNhmcTKRc+RSr9WxJzqa5tzsfTRpItzC9JxDXV9P3uSo66pGKDnE1KScLuXHuWjLzi7msQwDzJ/bDw2L4JnciIi4t73Qpd87fQEJyNi283flQhYc0AC5zOKCIOJeTBSVMmL+BzPxiuoT48MYdfVRwiIjUAR8vd96/uz89WzfnVGEpt7+7Tms8pNHROwoR4XSplUnvb+RQZgFhfl68f3d/fLzcjY4lItJg+Hq5s/Du/vRu05zsisJji7bTlUZERYdII1dmtfHgRwlsSc7G18vC+3f3J9hXZ3GIiNQ1vybu/PeeAeW7Wp0uY/y769lwWCeXS+OgokOkEbPZ7Dy6eDsrE4/jYTHzzp196RisHdrEddwHxN53H5tvuQV+7ArcUtEq4pyaeVp47+5+DG7/ywGCPx/INDqWSL1T0SHSSNntdl5YupvPt6TiZjYx9/Y+DGjnb3QskRpZCnRdupTozz6DjvuAzypaRZxX5TkeQzsFUlRq5a73NvLDngyjY4nUKxUdIo3Uf1YdYMHPRwB4+eZLuFqH/4mIXDRe7m68fWc013QLpqTMxp/+u4kVu9KNjiVSb1R0iDRCC+OPOE4b//t13bipT7jBiUREGh9Pixtz/9iH0T1CKbXauf/DLSzZdszoWCL1QkWHSCPz1dZUnvlqFwAPX9WRuy6NNDiRiEjj5e5m5t+39uLG3q0os9l5+JMEPliXZHQskTqnokOkEYndfZy/froNgImD2zLl6o4GJxIREYubmVdu6ckdA9tgt8PfvtzJ66v2o/ObpSFR0SHSSPywJ4P7P9xMmc3Ojb1b8cy13TCZTEbHEhERwM1s4oXro/jLlR0AeGXFPv6xNBGbTYWHNAwqOkQagTX7T3DfB5sptdoZ3SOUl2++BLNZBYeIiDMxmUz8NaYzT1/bDYB5Px3mkc+2U2a1GZxM5MKp6BBp4NYezGTS+5soKbMxvHsws2/thcVN//RFRJzVPZdF8uotPXEzm1i85Sh//nALp0utRscSuSB65yHSgG04fJJ73ttEcZmNq7oE8Z/b+uCugkNExOmNjQ7nzTui8bCYid19nIkLNpB3utToWCK1pncfIg3U5qRT3LVgA0WlVoZ2CmTuHX3wsOifvDQstwE7b7uN9ffcA3v7APdUtIq4vmu6BfP+Xf1p5mlh3aGT/OGtdRzPPW10LJFaMdm1NUK9yc3Nxc/Pj5ycHHx9fY2OI43IpiMnuWvBRvKKy7isQwDvTuiLl7ub0bFERKQWdqbmMHHBRjLziwnz82LBXf3pHOJjdCxp5Gr6Plcfe4o0MGsPZDJ+3gbyissY2K4l79ypgkNExJVFtfLji/sH0y6wKcdyTnPzm2tZeyDT6FgiNaKiQ6QB+WFPBhPf20hRqZXLOwWyYGJ/mnio4BARcXWtW3rz+Z8H069tC/JOlzFhwQa+SDhqdCyR86aiQ6SB+HZnGn/6b/kuVdd0C+adO6NVcIiINCDNvT347z0DGH1JKKVWO1MXbWPODwd0iKC4BBUdIg3AV1tTeeCjBEqtdq69JJS5f+yDp0UFhzR8XYB9XbqQ7+sLhzwB34pWkYbJy92N/9zamz9d3g6Al7/byxOf76CkTGd5iHNT0SHi4t77+TBTFm3FarNzc3Q4/761t7bFlUYjH/DOz6dZXh40KQPyKlpFGi6z2cSTo7ry3JjumEzwycYUxs9bz8mCEqOjiZyV3pmIuCi73c5L3+7h2a93Y7fD+IERvDT2Etx00riISKMwYXBb5k3oSzNPC+sPn2TM6z+xJz3X6Fgi1VLRIeKCSq02HvlsO3NXHwRgekwnnr++O2YVHCIijcqVXYL54v7BRPh7c/RUEWPnrmXFrnSjY4mcQUWHiIspLCnjTws38dnmo7iZTcwc24MHr+yIyaSCQ0SkMeoY7MOX91/K4Pb+FJRYue+DzVpgLk5HRYeIC0nLKeIPb8Xzw94TeLmbeXt8NOP6tTE6loiIGKxFUw/ev7s/dw6KwG4vX2D+4EcJ5J0uNTqaCKCiQ8RlbEvJ5vrXf2Znai4tm3rw4aSBXNU12OhYIiLiJNzdzDx/fRT/vDEKdzcTS3ekcf3rP7M3Pc/oaCIqOkRcwTfbj/GHt+LJyCumU3AzvnrgUqIjWhgdS0REnNAfB0Sw6L5BhPp5cSizgOvn/MTnW3SQoBhLRYeIE7PZ7Pxf7D4e/CiB4jIbV3QOZPGfB9O6pbfR0URExIn1adOCpQ8NYUjHAE6X2pj26Tae/GIHp0utRkeTRkpFh4iTOlVQwt3vb+Tf3+8HYNJlkbw7oR8+Xu4GJxMREVfQsqkH793Vn4ev6ojJBB+tT+bGuWvZf1zTreTiM9m1tUG9yc3Nxc/Pj5ycHHx9fY2OIy5kW0o293+4hdTsIjwtZv5xQxS39G1tdCwRp/MN0Pybb2hSVER0xA7o3wNoAlxrcDIR5xK37wRTF23lZEEJnhYzfxvdlTsGRmjnQ6m1mr7PVdFRj1R0SE3Z7XY+WJfEC98kUmK10dbfm7l/jKZbmP7/ERGRC5ORd5rp/9vOj/tOAHB11yBmjr0E/2aeBicTV6Siw4mo6JCaOFVQwpNf7GD5zvJDnYZ3D+blW3riq+lUIiJSR2w2O++tPcK/lu+hxGojoJkn/7ihOyOiQo2OJi5GRYcTUdEh52vN/hP89dNtZOQVYzGbeGxEFyYNidSwt4iI1IvEtFwe/iSBfcfzARjdI5Rnx3Qn0EejHnJ+VHQ4ERUd8nuKSqy89N0eFvx8BIB2gU3597je9Aj3MzaYiIvYDLhv3oxHSQldmh+Eru0BDyDa4GQizq+4zMp/vj/AG3EHsdrsNPd259nrunN9rzB96CW/S0WHE1HRIefy84FMnvh8B8knCwEYPzCCJ0d1pYmHm8HJRFxHOLAuPJzw1FQ4ZoZQG9AK0JkEIudrZ2oOj3y2ncS0XACGdAzg2THdaR/YzOBk4sxq+j5XW+aKXGTZhSU88r9t/PHd9SSfLCTUz4sFE/vxwg1RKjhEROSii2rlx5IHL2V6TCc83Mys2Z/JiNk/8q/leygoLjM6njQQKjpELhKrzc6ijclcPSuO/20+iskEEwZFsGLq5VzRJcjoeCIi0oi5u5l58MqO5b+TOgdSarXzZtxBrno1jq+2pmKzaWKMXBiL0QFEGoONR07y3Ne72JlaPnTdIagZM8f2IDqipcHJREREftE2oCnzJ/bj+8QMnvtmFykni3j4k628s+YQj43owpCOgUZHFBelokOkHh08kc+s2H0s3Z4GgI+nhYev7siEwW1xd9NAo4iIOB+TycTV3YK5rGMAb/94iLfiDrIzNZfx8zZwaQd/HhvRhUvCmxsdU1yMFpLXIy0kb7yOnirk3yv3s3jLUWx2MJng1n6t+WtMZwJ0CJNIndFCcpH6l5lfzOurDvDh+iRKreVvG6/qEsT9V7TXiH0jVtP3uRrpEKlDh07k886aw3y2OcXxg/nqrkFMu6azThUXERGXFNDMk2fHdOeeyyKZFbuPL7em8v2eDL7fk8GAyJbcf0UHLu8YoG125Zw00lGPNNLReCQkn+KtuEN8tzudyn9Rl3bw568xnenTpoWx4UQaMI10iFx8h07k81bcIT5POOr4gK1LiA93DmrL9b3CaOqpz7QbA53T4URUdDRsRSVWvt5+jA/XJ7MtJdvRflWXIO4b2p7+kRpyFqlvKjpEjHMsu4h31xzm4w3JFJVagfK1i2Ojw7ljYBs6BPkYnFDqk4oOJ6Kio+Gx2+1sTcnmy4RUPk9IJe90+f7l7m4mbujVij9d3o6OwfohK3KxqOgQMV52YQmfbT7KB+uSOJJV6Gjv2bo5N/QK47qeYVrP2ACp6HAiKjoajr3peSzZlsrX29IcJ4gDRPh7c1v/NtwcHa4fqCIGyAPseXmY7HZ8TPng0wwwASr+RS42m83OTwcy+e+6JFbtycBacbaHm9nEkI4BjO4RypVdgvDX78sGQUWHE1HR4bpKymxsPHKSVXsy+GFPBocyCxzf8/Zw45puwYztE85lHQIwm7VwTkRE5NdO5BXzzfZjfLn1WJUpyCYT9GnTgqu7BnNV1yA6BjXTAnQXpaLDiajocB1Wm53EtFzWHz7J+kNZrD2YRX5xmeP7Hm5mhnYOZEzPMK7qGoS3hxbJiYiInI/DmQUs2XqM2MR0xyG5lQJ9PBnYzp9B7fwZ3N6fCH9vFSEuQkWHE1HR4ZzsdjtpOafZdSyXnak5bDuazeYjp8j7VZEB5VsEXtE5kCu7BHFpxwB8vdwNSiwiItIwHMsu4vs9GcTuPs76Q1kUl9mqfN+/qQeXhPvRs3VzeoY355JwP03HclIuV3TMnTuXl19+mbS0NLp3787s2bMZMmTIWfvHxcUxbdo0du3aRVhYGI8++iiTJ0+u0mfx4sU8/fTTHDx4kPbt2/PPf/6TG2+8sUaPa7fbee6553j77bc5deoUAwYMYM6cOXTv3v28n5uKDmPZ7XbSc09z+EQBhzILOJxZwL7jeew6lsvJgpIz+vt4WujbtgX9I/25tIM/UWF+mjol4uRmAd1nzcI3N5dBwxJgWG/AF5hmcDIR+T2nS61sTclm7cEs1h3MIiHllGML3l8L9vWkY5APHYKa0TG4GR2DfGgb4E1gM0+NihjIpYqORYsWMX78eObOncull17KW2+9xbvvvsvu3btp06bNGf0PHz5MVFQU9957L/fddx8///wz999/Px9//DFjx44FID4+niFDhvDCCy9w44038sUXX/DMM8/w008/MWDAgPN+3JkzZ/LPf/6T9957j06dOvGPf/yDH3/8kb179+Ljc34LFFV01B+bzU7e6TIyC4pJzzlNWs5p0nOKSM89TXrOaVKzT3Mks8Cxhd9vuZlNdAxqRlQrP6LCfOnbtiVdQ31xU5Eh4lK0e5VIw3G61EpiWi7bUrLZfrR8JsLBEwVn7e9pMdOqRRNat/AmvEUTWrVoQpCPF4E+ngQ08yCwmSctm3pgcTNfxGfReLhU0TFgwAD69OnDG2+84Wjr2rUrN9xwAzNmzDij/2OPPcaSJUtITEx0tE2ePJlt27YRHx8PwLhx48jNzWX58uWOPiNGjKBFixZ8/PHH5/W4drudsLAwpkyZwmOPPQZAcXExwcHBzJw5k/vuu++8nl9jLzrsdjtlNjulVhulVjtlFX+WWm2O9qISK4UlVgpLyigssVZ8XUZBxd8LSsrIKSwlu6iUU4Ul5BRW/FlUiu08/s91M5to09KbyICmtAtoSrvAZnQP86VziA9e7m71/yKISL1S0SHSsOWdLuVARj77M/I5kJHPvuN57D+eT1pO0Xm9DzCZoKW3B8293fHxcse3iTs+XhZ8vdzxbVL+p4+XBS93t/KbxfzL390r/m4p/7uHxYzFzYzFbMLNbMJiNjXqkZaavs81bDVsSUkJmzdv5vHHH6/SHhMTw9q1a6u9T3x8PDExMVXahg8fzrx58ygtLcXd3Z34+HimTp16Rp/Zs2ef9+MePnyY9PT0Ko/l6enJ0KFDWbt27VmLjuLiYoqLix1f5+bmVtvvYlh/KIuXv9uLHbDZ7djtYAew27HZwU55m81eXhzwm362ir/YKf/+r+9jr7jPb69ts9kpsdoo+1VhUd98PC0E+3kR6udFiG/Fn35NCPXzIsLfm9YtvXHXJxwiIiIuycfLnd5tWtC7TYsq7SVlNtJzTnP0VCFHTxWV/5ldxIm8Yk7kFZOZX8LJgmJsdsgqKCGrmmnVdcFsAovZjMXtl0LEzfxLYWI2gwkTJhOYTSZMAKbyjb1NJhNm0y/fL79e+d9Nv2o3VdzP9Kv7VZY6wb5ezPljn3p5bnXNsKIjMzMTq9VKcHBwlfbg4GDS09OrvU96enq1/cvKysjMzCQ0NPSsfSqveT6PW/lndX2SkpLO+pxmzJjBc889d9bvX0zZRaVsSjpldIwzWMwmLG4m3Cv+gTZxd8Pb04K3h1v53z0qvq74exMPC8293WnexJ3m3h608HanRVMPmjdxx8/bHU+LRitEREQaGw+LmTb+3rTx9z5rH6vNzsmCEjLzi8kuLCXvdCm5p8vK/ywqI/d0eVve6TKKSq2cLrVyutTG6VIrxWW2iq8r2sqsVDc3yGaHEquNkupnc9e7Ni3P/vydjeH7fv52WMput59zqKq6/r9tP59r1lWfX3viiSeYNu2XxYu5ubm0bt36rP3rU6/WzXnzjj6/qo7L/6ysuPlVxX1m9V1ReZsqK/Pyb5iquQ/8Uo27mU24u5lwdzPj7mZ2FBfuFhMWsxl3t8Y9DCkiIiIXj5vZRKCPJ4E+F777ld1ux2ornzZutdkps9ops9kcbWf7unzSxy+zQspnmVR+/etZJRXt/DKbhIo+NhtV2n9d/DTxcJ0PXw0rOgICAnBzcztjVCMjI+OMEYZKISEh1fa3WCz4+/ufs0/lNc/ncUNCQoDyEY/Q0NDzygblU7A8PZ1jW7dgXy9GRIX+fkcREREROSeTqXymhiZY1J5hk909PDyIjo4mNja2SntsbCyDBw+u9j6DBg06o/+KFSvo27cv7u7u5+xTec3zedzIyEhCQkKq9CkpKSEuLu6s2UREREREpHqGTq+aNm0a48ePp2/fvgwaNIi3336b5ORkx7kbTzzxBKmpqSxcuBAo36nq9ddfZ9q0adx7773Ex8czb948x65UAA8//DCXX345M2fO5Prrr+err75i5cqV/PTTT+f9uCaTiSlTpvDiiy/SsWNHOnbsyIsvvoi3tze33377RXyFRERERERcn6FFx7hx48jKyuL5558nLS2NqKgoli1bRkREBABpaWkkJyc7+kdGRrJs2TKmTp3KnDlzCAsL47XXXnOc0QEwePBgPvnkE/72t7/x9NNP0759exYtWuQ4o+N8Hhfg0UcfpaioiPvvv99xOOCKFSvO+4wOEREREREpZ/iJ5A1ZYz+nQ0Skvo0BHhkzhsATJ+gy+zAMiAQCgSUGJxMRadhc5pwOERGRC7UEYIkKDBERZ6dT00REREREpF6p6BARERERkXqlokNEREREROqVig4REXFZY4A1Y8awZ9AgWB8CDKpoFRERZ6KF5CIi4rK2AJFbthCemgptzMBxoJXBqURE5Lc00iEiIiIiIvVKRYeIiIiIiNQrFR0iIiIiIlKvVHSIiIiIiEi9UtEhIiIiIiL1SkWHiIiIiIjUKxUdIiIiIiJSr3RORz2y2+0A5ObmGpxE5P/bu/+Yqur/D+DPS5/LhQgIvOHlhiKjjH28BAGmuFLCRTKQnIuk2sJVbDavQNEmVg7sxzK3tC1zaDlWq4V/hM5N+wEJGCOTARVQGcQVlB8yncINAi7c1+ePz7jfzxG6XPzey73o87Hd7e593pe97mvPc89933PPhejmZAVgtloxCABmAfwmR/m6S0TkSpPvbyff786Eiw4XMpvNAIBFixa5uRIiopvXvyfv3Dd54OsFEOieYoiIbjFmsxmBgTO/5qrE0eUJzZrVakVPTw/8/f2hUqnszh0cHMSiRYtw4cIFBAQEzFGFNzf21LnYT+diP52PPXUu9tO52E/nY0+da7b9FBGYzWbo9Xp4ec18xQbPdLiQl5cXwsLCZvWYgIAA7jhOxp46F/vpXOyn87GnzsV+Ohf76XzsqXPNpp+OnOGYxAvJiYiIiIjIpbjoICIiIiIil+Kiw0NoNBoUFRVBo9G4u5SbBnvqXOync7GfzseeOhf76Vzsp/Oxp87l6n7yQnIiIiIiInIpnukgIiIiIiKX4qKDiIiIiIhciosOIiIiIiJyKS46iIiIiIjIpbjo8ABLliyBSqVS3AoLCxVzurq6sH79evj5+UGr1SI3NxdjY2NuqtiznT9/Hs8//zwiIiLg6+uLyMhIFBUVTenX9T1XqVQoKSlxU9We78CBA4iIiICPjw/i4+Px/fffu7ukeeGdd97B8uXL4e/vj5CQEGzYsAHnzp1TzNm8efOULK5cudJNFXu24uLiKb3S6XS27SKC4uJi6PV6+Pr6IikpCa2trW6s2LNNd/xRqVTYunUrAGbTEadPn8b69euh1+uhUqlw7NgxxXZHMjk6Oopt27ZBq9XCz88PGRkZuHjx4hw+C89hr58WiwXbt29HdHQ0/Pz8oNfr8eyzz6Knp0fxN5KSkqbkNisra46fiWeYKZ+O7OPOyicXHR7ijTfeQG9vr+32+uuv27ZNTEwgLS0NQ0NDqK2tRVlZGb788ksUFBS4sWLP9fvvv8NqteLgwYNobW3Fvn37UFJSgldffXXK3NLSUkXfs7Oz3VCx5zty5Ajy8/Px2muvoampCQ8//DBSU1PR1dXl7tI8Xk1NDbZu3YozZ86goqIC4+PjSElJwdDQkGLeunXrFFk8efKkmyr2fMuWLVP0qrm52bZtz5492Lt3L/bv34/6+nrodDo8+uijMJvNbqzYc9XX1yt6WVFRAQDIzMy0zWE27RsaGkJMTAz2798/7XZHMpmfn4+jR4+irKwMtbW1+Ouvv5Ceno6JiYm5ehoew14/h4eH0djYiJ07d6KxsRHl5eX4448/kJGRMWVuTk6OIrcHDx6ci/I9zkz5BGbex52WTyG3Cw8Pl3379v3j9pMnT4qXl5d0d3fbxr744gvRaDQyMDAwBxXOf3v27JGIiAjFGAA5evSoewqaZx588EHZsmWLYiwqKkoKCwvdVNH81d/fLwCkpqbGNpadnS2PP/64+4qaR4qKiiQmJmbabVarVXQ6nezevds2NjIyIoGBgVJSUjJHFc5veXl5EhkZKVarVUSYzdm6/rjiSCavXbsmarVaysrKbHO6u7vFy8tLvv766zmr3RM5cpw+e/asAJDOzk7b2Jo1ayQvL8+1xc1D0/Vzpn3cmfnkmQ4P8e6772LBggWIjY3F22+/rfgq0A8//ACDwQC9Xm8be+yxxzA6OoqGhgZ3lDvvDAwMIDg4eMq40WiEVqvF8uXLUVJSAqvV6obqPNvY2BgaGhqQkpKiGE9JSUFdXZ2bqpq/BgYGAGBKHqurqxESEoKlS5ciJycH/f397ihvXmhra4Ner0dERASysrLQ0dEBADCZTOjr61NkVaPRYM2aNcyqA8bGxvDZZ5/hueeeg0qlso0zmzfOkUw2NDTAYrEo5uj1ehgMBubWAQMDA1CpVLjzzjsV459//jm0Wi2WLVuGV155hWc77bC3jzszn/9yWsV0w/Ly8hAXF4egoCCcPXsWO3bsgMlkwscffwwA6Ovrw8KFCxWPCQoKgre3N/r6+txR8rzy559/4oMPPsB7772nGH/zzTexdu1a+Pr64rvvvkNBQQEuX76s+GobAZcvX8bExMSUDC5cuJD5myURwcsvv4yHHnoIBoPBNp6amorMzEyEh4fDZDJh586dSE5ORkNDA//T7nVWrFiBTz/9FEuXLsWlS5fw1ltvYdWqVWhtbbXlcbqsdnZ2uqPceeXYsWO4du0aNm/ebBtjNv9/HMlkX18fvL29ERQUNGUOX2PtGxkZQWFhIZ5++mkEBATYxp955hlERERAp9OhpaUFO3bswM8//2z7+iD9n5n2cWfmk4sOFykuLsauXbvszqmvr0dCQgJeeukl29j999+PoKAgPPHEE7azHwAUnzpNEpFpx29Ws+nppJ6eHqxbtw6ZmZl44YUXFHP/d3ERGxsL4L/X1nDRMb3rs3ar5c8ZjEYjfvnlF9TW1irGN23aZLtvMBiQkJCA8PBwnDhxAhs3bpzrMj1aamqq7X50dDQSExMRGRmJTz75xHbxI7N6Yw4fPozU1FTFWXVm0zluJJPMrX0WiwVZWVmwWq04cOCAYltOTo7tvsFgwL333ouEhAQ0NjYiLi5urkv1aDe6j99IPrnocBGj0TjjLyUsWbJk2vHJA2d7ezsWLFgAnU6HH3/8UTHn6tWrsFgsUz49uZnNtqc9PT145JFHkJiYiEOHDs3491euXInBwUFcunTplurrTLRaLW677bYpn2j09/ezT7Owbds2HD9+HKdPn0ZYWJjduaGhoQgPD0dbW9scVTd/+fn5ITo6Gm1tbdiwYQOA/35yHBoaapvDrM6ss7MTlZWVKC8vtzuP2ZydyV9Ws5dJnU6HsbExXL16VfFpcn9/P1atWjW3Bc8TFosFTz75JEwmE06dOqU4yzGduLg4qNVqtLW1cdExg+v3cWfmk9d0uIhWq0VUVJTdm4+Pz7SPbWpqAgDbC1RiYiJaWlrQ29trm/Ptt99Co9EgPj7e9U/GQ8ymp93d3UhKSkJcXBxKS0vh5TVz1JuamuDj4zPle6G3Om9vb8THx085LV1RUcEDogNEBEajEeXl5Th16hQiIiJmfMyVK1dw4cIFxZsUmt7o6Ch+++03hIaG2r5O8b9ZHRsbQ01NDbM6g9LSUoSEhCAtLc3uPGZzdhzJZHx8PNRqtWJOb28vWlpamNtpTC442traUFlZaftGiD2tra2wWCzMrQOu38edms9ZXXZOTldXVyd79+6VpqYm6ejokCNHjoher5eMjAzbnPHxcTEYDLJ27VppbGyUyspKCQsLE6PR6MbKPVd3d7fcc889kpycLBcvXpTe3l7bbdLx48fl0KFD0tzcLO3t7fLRRx9JQECA5ObmurFyz1VWViZqtVoOHz4sv/76q+Tn54ufn5+cP3/e3aV5vBdffFECAwOlurpakcXh4WERETGbzVJQUCB1dXViMpmkqqpKEhMT5e6775bBwUE3V+95CgoKpLq6Wjo6OuTMmTOSnp4u/v7+tizu3r1bAgMDpby8XJqbm+Wpp56S0NBQ9tKOiYkJWbx4sWzfvl0xzmw6xmw2S1NTkzQ1NQkA2zF98teUHMnkli1bJCwsTCorK6WxsVGSk5MlJiZGxsfH3fW03MZePy0Wi2RkZEhYWJj89NNPitfU0dFRERFpb2+XXbt2SX19vZhMJjlx4oRERUXJAw88wH5e109H93Fn5ZOLDjdraGiQFStWSGBgoPj4+Mh9990nRUVFMjQ0pJjX2dkpaWlp4uvrK8HBwWI0GmVkZMRNVXu20tJSATDtbdJXX30lsbGxcscdd8jtt98uBoNB3n//fbFYLG6s3LN9+OGHEh4eLt7e3hIXF6f4yVf6Z/+UxdLSUhERGR4elpSUFLnrrrtErVbL4sWLJTs7W7q6utxbuIfatGmThIaGilqtFr1eLxs3bpTW1lbbdqvVKkVFRaLT6USj0cjq1aulubnZjRV7vm+++UYAyLlz5xTjzKZjqqqqpt3Hs7OzRcSxTP79999iNBolODhYfH19JT09/Zbts71+mkymf3xNraqqEhGRrq4uWb16tQQHB4u3t7dERkZKbm6uXLlyxb1PzE3s9dPRfdxZ+VSJiMzu3AgREREREZHjeE0HERERERG5FBcdRERERETkUlx0EBERERGRS3HRQURERERELsVFBxERERERuRQXHURERERE5FJcdBARERERkUtx0UFERERERC7FRQcREREREbkUFx1ERERERORSXHQQEREREZFLcdFBREREREQu9R+K4pcjPGnVgwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def show_density(var_data):\n",
    "    import matplotlib.pyplot as plt\n",
    "\n",
    "    fig = plt.figure(figsize=(9,6))\n",
    "\n",
    "    var_data.plot.density()\n",
    "\n",
    "    plt.title('Data Density')\n",
    "\n",
    "    plt.axvline(x=var_data.mean(), color = 'cyan', linestyle='dashed', linewidth = 2)\n",
    "    plt.axvline(x=var_data.median(), color = 'red', linestyle='dashed', linewidth = 2)\n",
    "    plt.axvline(x=var_data.mode()[0], color = 'yellow', linestyle='dashed', linewidth = 2)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "col=df_students.Grade\n",
    "\n",
    "show_density(col)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "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": 2
}