{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4ab79e72",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import StandardScaler,MinMaxScaler,RobustScaler,Binarizer,Normalizer,OneHotEncoder,LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f9f419f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.882455</td>\n",
       "      <td>1.466990</td>\n",
       "      <td>-7.089363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.661740</td>\n",
       "      <td>0.571914</td>\n",
       "      <td>-3.105893</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.861542</td>\n",
       "      <td>7.828852</td>\n",
       "      <td>-1.039068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.504184</td>\n",
       "      <td>5.001904</td>\n",
       "      <td>-9.755722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.219220</td>\n",
       "      <td>1.731128</td>\n",
       "      <td>-7.679528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>-0.068972</td>\n",
       "      <td>3.739968</td>\n",
       "      <td>-4.303864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>-2.167260</td>\n",
       "      <td>0.681434</td>\n",
       "      <td>-9.584910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>2.188712</td>\n",
       "      <td>9.860986</td>\n",
       "      <td>-9.986860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>0.595445</td>\n",
       "      <td>5.982577</td>\n",
       "      <td>-11.128039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>0.122246</td>\n",
       "      <td>9.105143</td>\n",
       "      <td>-6.612080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             A         B          C\n",
       "0     0.882455  1.466990  -7.089363\n",
       "1    -0.661740  0.571914  -3.105893\n",
       "2     4.861542  7.828852  -1.039068\n",
       "3    -0.504184  5.001904  -9.755722\n",
       "4     0.219220  1.731128  -7.679528\n",
       "...        ...       ...        ...\n",
       "9995 -0.068972  3.739968  -4.303864\n",
       "9996 -2.167260  0.681434  -9.584910\n",
       "9997  2.188712  9.860986  -9.986860\n",
       "9998  0.595445  5.982577 -11.128039\n",
       "9999  0.122246  9.105143  -6.612080\n",
       "\n",
       "[10000 rows x 3 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(5)\n",
    "a = np.random.normal(0, 2, 10000)  # normal data genration ko lagi (0 -> mean center point , 2, std \n",
    "b = np.random.normal(5, 3, 10000)\n",
    "c = np.random.normal(-5, 5, 10000)\n",
    "\n",
    "df = pd.DataFrame({\n",
    "    'A' : a,\n",
    "    'B' : b,\n",
    "    'C' : c\n",
    "})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5881bcf4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "34e44654",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7d99c474",
   "metadata": {},
   "outputs": [],
   "source": [
    "scaled = scaler.fit_transform(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ec5e6f04",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(scaled, columns=['A','B','C'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9b691626",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "83da7089",
   "metadata": {},
   "outputs": [],
   "source": [
    "minmax = MinMaxScaler()\n",
    "mm_scaled = minmax.fit_transform(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "80dbb17b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jIiGnc/K+MfFjcNgcsPNVAF5omoZhwD1X5Zzu8DOakB7L2JRo3vNPZnJ7YLTVtqptmKZ5foWLSEhQuBGRkLOvdh9wrL9NQxmUfIgfgzd9M/nExDRGJ51mkcyzdG1eKh/48hnf3oHLNIOT+YlI76qoqODee+9l1KhRuN1uMjMzufHGG3nnnXf67JwKNyIScvbX7gdgzNAxsO9tALaaYzhCAndelN0r57g2L5UtZg4e080E3ZoS6ROFhYVMnz6dd999l1/84hds376dt956iyuvvJJvfOMbfXZezXMjIiFnX12g5SYnPge2PwHAe95J5CRHM33E0F45R156LMnxMaxrHsfk9iK2RLg1mZ9IL/v617+OYRisW7eOqKio4Pa8vDy+/OUv99l5FW5EJKS0eFo43HgYgJzYUXBwJQD/9k/k/12Y1WsLXBqGwZzxyXywLo8L2/ZCHJrMTwYE0zRp9bZacu5IR+RZfwdramp46623+OlPf9ol2HSKj4/v5eo+pnAjIiHlUP0hTEwSIhJIrC2CtnrqzSHsYBS/m5Leq+e6OGcYv/lwAl9tfxn4eDK/KOfJP4hFQkWrt5WZL8605Nwfff4jhjiHnNW++/fvxzRNxo0bd+ade5n63IhISOlyS+rAuwB84M/nwtHJDIt29+q5Zo1KZDcjiPI6SPN6NZmfSC/qHH3YW62tPaGWGxEJKZ2diXPic2DPBwCs8efxiYm922oDEBfpZEJGIlsqcpjcVkF5tIOtVVuZmWbNv4pFzkakI5KPPv+RZec+W2PGjMEwDAoKCrj55pv7rqhuKNyISEjZX3dspFT8aPwlv8YGbCaXb+el9Mn5Lh6dyIbyXCa3F/NWdJRGTEnIMwzjrG8NWSkhIYFrr72WJ554gvvuu++kfjd1dXV91u9Gt6VEJKQEb0uZDmyeZprMCBJHTiaxl29Jdbpo9DA2+McySZP5ifS6J598Ep/Px4UXXsjy5cvZt28fBQUFPP7448yePbvPzqtwIyIho769nsqWSgBy6ioA2OzP4fpJGX12zilZ8Ww1cxjb5sHl12R+Ir1p5MiRbNq0iSuvvJLvfOc75Ofnc8011/DOO+/w1FNP9dl5dVtKRELGgboDAKRFpcGhjQBsYSxfzEvts3NGux1kpKZy4GgWEzragvPdZMdl99k5RQaTtLQ0fvOb3/Cb3/ym386plhsRCRmdyy7kxOfgKw50mGxKmsbQKFefnndG9lA2+McG15lSvxuRgU3hRkRCRrC/TUwWca0lAGTkX9Ln550+Yiib/WOY3KZwIxIOFG5EJGQU1hcCMNxrB6DcTOCyyWP7/LzTsoay1RzN1GMtN/tq91HfXt/n5xWRvqFwIyIho6gx0JHXVn4UgBJHNiMS+3624IyhkbREZeH0RpDd4cHEZNORTX1+XhHpGwo3IhIS2rxtVDQHRkgNKS0GwJ88oV/ObRgG00cmss0/igva2gBYf2R9v5xbRHqfwo2IhITOxTKjndEk1wZGTSXnTO2380/NDNyauuBYv5sNFRv67dwiZ2MwzL/UW9eocCMiIaHzllSCK50xZqAz8YjxF/Tb+SdlxLHVP5oZx1pudtfsVr8bCQl2e6APWkdHh8WV9L3Oa+y85nNl6Tw3ixcv5pVXXmH37t1ERkZy0UUX8fOf/5zc3NxTHrNy5UquvPLKk7YXFBRYsvKoiPSO4obArShHezTxRjM+7NiT++87nT88jm3maJJ8frI9HgqdTjYd2cSVWSf/vBHpTw6HgyFDhlBVVYXT6cRmC892Cb/fT1VVFUOGDMHhOL94Ymm4WbVqFd/4xje44IIL8Hq9fP/732fu3Lns2rXrpDUoTrRnzx5iY2ODz5OSkvq6XBHpQ52zAttqfQC0xmQT7eibJRe6E+V2EJuUSXl9Ahe0tlHodLL+yHqFG7GcYRikpaVx6NAhiorCe/Zsm81GVlbWea8kbmm4eeutt7o8X7p0KcnJyWzcuJHLLrvstMcmJyf32YJbItL/ShoDt6KSmloAcA/P7/caJmXEs7V2NBe07eTPsTHqdyMhw+VyMWbMmLC/NeVyuXqlZSqkll+orw/c305ISDjjvlOnTqWtrY0JEybwX//1X93eqgJob2+n/djcFQANDQ29U6yI9KrOlps8X+A76kyb2O81TMqIY9vWUXy5LbD0Q2e/mzh3XL/XInIim81GRESE1WUMCCFz4840TRYsWMAll1xCfv6p/8WWlpbGM888w/Lly3nllVfIzc1lzpw5rF69utv9Fy9eTFxcXPCRmZnZV5cgIueo1dvKkZYjAMz0BP6flP4ZBn68SRlxbDVHMcznZ6QPzXcjMkCFTMvNPffcw7Zt23j//fdPu19ubm6XDsezZ8+mpKSERx55pNtbWYsWLWLBggXB5w0NDQo4IiGm85YUvgimmAfBAPppjpvjjU+LZTejALiguZFDsTHqdyMyAIVEy829997L66+/znvvvUdGRkaPj581axb79u3r9jW3201sbGyXh4iEluBIqY5YIgwvpjMK4kf0ex0RTjupqWmU+JM0343IAGZpuDFNk3vuuYdXXnmFd999l5EjR57T+2zevJm0tLRerk5E+ktxYyDcJHgCq38bKRPAouGukzLi2Glma74bkQHM0ttS3/jGN3jxxRf561//SkxMDBUVganX4+LiiIyMBAK3lUpLS3nuuecAeOyxx8jOziYvL4+Ojg6ef/55li9fzvLlyy27DhE5P50tNxkeb2CDBbekOk3KiGfHxmyu860n24ig0Gxjc+Vmrsi8wrKaRKRnLA03Tz31FABXXHFFl+1Lly7lzjvvBKC8vJzi4uLgax0dHSxcuJDS0lIiIyPJy8vjjTfe4Prrr++vskWklx2sKwRgnKc5sCElz7JaJg6P420zG4AZHV4KnYFbUwo3IgOHpeHmbNaQWLZsWZfn999/P/fff38fVSQiVugMNzP9gdXArWy5GZMSzR4jcIt8et0R/pKUyMYjGy2rR0R6LiQ6FIvI4NXiaaHeEwg10z2VgY0Wtty4HXbik7OoMuOY0Rrod1NQU0BzZ6uSiIQ8hRsRsVTnMHCbz02c3w/RqTDkzBN59qW89Fh2+LNJ9fkY7ozFZ/rYXLnZ0ppE5Owp3IiIpfbXFgIQ23Fs5lULJu87UV56LDvMwK2pGcYQQEPCRQYShRsRsdRHJXsAyPAd22Bhf5tO+cPj2OnPBmB6c2A5CPW7ERk4FG5ExFI7qw4AkGceWwPOwv42ncanxbKzc8RUZWDNqx1Hd9DqbbWwKhE5Wwo3ImKpw02BPjcTO2oCG0Kg5SbK7cCZkE29OYSMjlZS3Al4/V62Vm21ujQROQsKNyJiGb/fpNkfWChzdFsDGDZIyj3DUf0jLyOenf5sDGBaRAoA26q2WVuUiJwVhRsRsczOikoMR6BPS6bXAwmjwRlpcVUBeekf35qa6A3MybW9aruFFYnI2VK4ERHLrDq4G4BIv5M4vxkSI6U65aXHUuDPAmBiYy0A26q3ndXkoyJiLYUbEbHM5vJ9AAz3H5ssPSXfwmq6ykuPY7cZCDfjjuzDYXNQ01ZDaVOpxZWJyJko3IiIZTrnuBnt8wQ2hEBn4k4JUS6aY0bjMe1EtNWRGxuY92Z7tW5NiYQ6hRsRsUSH109VW6AVZHRrXWBjCN2WAhgzfBgHzHQAJrqTAHUqFhkIFG5ExBJ7jzRiOqsByO5oA2cUxGdbW9QJ8tJj2W1mAjDJbwfUciMyECjciIglth6uw+YKhJssjweSx4EttH4k5aXHsvtYp+JJTXUAFBwtwNN5G01EQlJo/SQRkUFjU0k5NkcTAFkeL6ROtLiik+UPj6PAHAFARuVeYl2xdPg72Fe3z+LKROR0FG5ExBI7qw4BEG/aiDFNSJ9qcUUnS4uLoNw9CgDb0QOMGzoWgD01e6wsS0TOQOFGRPqdz29S3FAMwAhPR2Bj2hTrCjoFwzBITs+mxozGMP3kuocBsKdW4UYklCnciEi/K65pwWurBGBEexvYXSE1DPx4ecPjgv1uxpmBTsW7a3ZbWZKInIHCjYj0uz0VDcHOxCM83sDkfQ6XxVV1L++4fje5zY0A7K3Zq5mKRUKYwo2I9LuC8kZsrqMAZHm9kD7F2oJO4/jh4COPFuGwOWj0NFLWXGZxZSJyKgo3ItLv9lQ0Yhw/DDwEOxN3yk6M4qAtGwB7xQ5y4nIA3ZoSCWUKNyLS73YdOYLN0Qwcuy0Vgp2JO9ltBrbkcfhMA3tbLWNjAq04e2v2WlyZiJyKwo2I9KuWDi+lTSUAJHp9RNlckDze4qpOb1RaEgePLcMwxogE4ED9AStLEpHTULgRkX6190gTxrH+NiO8HkjNB7vT4qpOb3xaTLDfzaj2NgAO1CnciIQqhRsR6Ve7yxuOW3bBG9L9bTqNT4ul4Nhw8JyGKgAKGwrx+r1WliUip6BwIyL9al9lEzbnceEmhPvbdBqXGstuMxBuko7sIdIRidfvpbix2OLKRKQ7Cjci0q8OVDV9PAw8xEdKdYob4qQ2JhcA+9H9jIodCcDBuoNWliUip6BwIyL9an9lEw5X4NbOCNMOSeMsrujsJKRmU28OwWZ6GR2RCKjfjUioUrgRkX7T2uGjtKEG09EKQFZiLtgdFld1dsanxwVvTY0yAzVrxJRIaFK4EZF+c7C6CeNYf5skr5ch6dMtrujsjUuLCXYqHt0amKNHt6VEQpPCjYj0m/2VH/e3yfQOjM7EncanfdypeERdBQDFjcVaY0okBCnciEi/OVDVjK2zv80AGQbeKTsxikJbINykHtmH3bDT6m2lsqXS4spE5EQKNyLSbw5UNhHrOgxAlg8YNtbagnrAbjMgKTCTcmTLEYZHpQJoOLhICFK4EZF+c6CqCbfrCAAjYjIGTGfiTtnDUynxJwGQ5YwHoKihyMKKRKQ7Cjci0i98fpOD1c10uBoByErKt7iinhuX+vEyDCMIBLPiBrXciIQahRsR6RclNS14zEba7D4ARgyfbXFFPTc+LZY9x8JNVntgOLtabkRCj8KNiPSLA1VN2F2BzrdpXi8RGRdaXFHPjUuLZY8/EG4y6gLXoj43IqFH4UZE+sX+yiZS3PsAyPb6YdgYiyvqubhIJ0ejcgAYcbQQCNyW8pt+C6sSkRMp3IhIvzhQ1USCqxCAbNdQsNmtLegcuVNz6TDtDG9rwGE46PB3UNFcYXVZInIchRsR6RcHqpqxuwO3crJjs60t5jzkpMZzwEzHAWS4hwLqdyMSahRuRKRfHKhqotUVWLYgO2WyxdWcu7EpMcFOxSMMN6ARUyKhRuFGRPpcTXMHjS3NVDoDfVOysy61uKJzNzYlhj3H1pjK8ngAKGpUy41IKFG4EZE+d7CqiRGuPXgNgwi/SerwmVaXdM7GpEQH57rJaKoFoKShxMqSROQECjci0ucOVjWTGbEbgCzDhc3utLiiczfE5aAhNjDSK7O+HIDDTYetLElETmBpuFm8eDEXXHABMTExJCcnc/PNN7Nnz54zHrdq1SqmT59OREQEo0aN4umnn+6HakXkXB2obiLGFWjdyI4YZnE1529o6kgazCFkeNoBKG0q1ergIiHE0nCzatUqvvGNb/Dhhx+yYsUKvF4vc+fOpbm5+ZTHHDp0iOuvv55LL72UzZs3873vfY/77ruP5cuX92PlItITB6uaMVzVAGTHj7a4mvM3JjWWPWYG6V4vAK3eVmrbay2uSkQ6Wbpq3VtvvdXl+dKlS0lOTmbjxo1cdtll3R7z9NNPk5WVxWOPPQbA+PHj2bBhA4888gi33nprX5csIufgUGU9w6PbABfZKVOsLue85abEsMefyQW2vSTbIqj0t1HaWEpCRILVpYkIIdbnpr6+HoCEhFP/gFi7di1z587tsu3aa69lw4YNeI6NXDhee3s7DQ0NXR4i0n88Pj9GzSFKnIEfN9kDuDNxp+OHgw/3G0Dg1pSIhIaQCTemabJgwQIuueQS8vNPvVpwRUUFKSkpXbalpKTg9Xqprq4+af/FixcTFxcXfGRmZvZ67SJyaiU1LeTY9lLlCDQUh8NtqVFJUeztDDdtLYA6FYuEkpAJN/fccw/btm3jpZdeOuO+hmF0ed7Zke/E7QCLFi2ivr4++Cgp0ZBNkf50sKqZVPd+ABINFzGuGIsrOn8RTjutCeMAyGgNtAar5UYkdFja56bTvffey+uvv87q1avJyMg47b6pqalUVHRdx6WyshKHw0FiYuJJ+7vdbtxud6/WKyJn72B1E9GuQKtGdmSSxdX0nvSUNMobExjuPTZiqlHhRiRUWNpyY5om99xzD6+88grvvvsuI0eOPOMxs2fPZsWKFV22vf3228yYMQOnc+DOnSESrg4cacLvDowkyo7Psbia3jM2NdCpePixEVNquREJHZaGm2984xs8//zzvPjii8TExFBRUUFFRQWtra3BfRYtWsTtt98efD5//nyKiopYsGABBQUFPPvssyxZsoSFCxdacQkicga1lcVUOn0AZCdPsria3pObEsNuM5MMTyDclDWX4fP7LK5KRMDicPPUU09RX1/PFVdcQVpaWvDx8ssvB/cpLy+nuPjjRelGjhzJm2++ycqVK5kyZQo/+clPePzxxzUMXCRERR7dSeGxVtXshLEWV9N7xqZEs8efSbLPh8MEr99LZUul1WWJCBb3uTmbGT2XLVt20rbLL7+cTZs29UFFItKb6ls8DG/fz1rnsZFSsdnWFtSLsodFccDIwg6k+fyUOGwcbjpMWnSa1aWJDHohM1pKRMLPgeomUpxFtNpsODAYHjPc6pJ6jdNuw584Fq9pY/hxyzCIiPUUbkSkzxyobMLtPgJARsQwnLbw6vQ/Mi2RQjOV4Z5AXxuFG5HQoHAjIn3mYFUjHlcdANmxI6wtpg/kpkQHOhV3jpjScHCRkKBwIyJ9pr78IKWdyy4kTrC4mt43JkXDwUVCkcKNiPSdqr0UdnYmjh9lcTG9L/fYGlOd4UZLMIiEBoUbEekTXp+fmKaDHw8Dj8u2tqA+kJkwhEP2EQw/NtdNVUsVHb4Oi6sSEYUbEekTh2tbGU4xZQ47EF7DwDvZbQYRSaNw+5xE+v2YmFQ0V5z5QBHpUwo3ItInDlY3Ee0uwzQMYuxuEiISrC6pT4xJjWO/mUG6bk2JhAyFGxHpE/uONGG4qgHIjsrAMAyLK+obucc6Fad7A8PBy5rKLK5IRBRuRKRPlJYeprpzTakwWnbhRGNTA52KO1tuFG5ErKdwIyJ9wnOk4OORUkPDZzXwE524gKaGg4tYT+FGRHqd32/irt338UipMOxM3CktLoIyZ3aw5aa0scTiikRE4UZEel1pXSuZ/pJgy82IMJyduJNhGCSmZBDrCQS5MoUbEcsp3IhIr9tX2Uiq/TANdjsG4R1uAMamxtLiSQGgqr2Odl+7xRWJDG4KNyLS6/YdacLhrgQgzZ1IhCPC4or6Vm5KNBXe4Qzx+wEobyq3uCKRwU3hRkR6XWF5Jc2uFiA8l1040djUGA6Ywz/ud6NOxSKWUrgRkV7XXr77487EQ8dYXE3fy02JYb+ZwfBjc90o3IhYS+FGRHqV32/irN03KDoTd0qMdlMdkR1cY6qsUbMUi1hJ4UZEelVpXStZ/hKKBsEw8OPFpWQzLJBtKKvZa20xIoOcwo2I9Kp9lY2MMkop7pzALwxXA+/O2LQ4bJ44AEobii2uRmRwU7gRkV6170gTsc4yvIaBy3CQGpVqdUn9YmxKDC2eZABK26osrkZkcFO4EZFeta+8Bq+rDoCsmAxsxuD4MZObGk1deyYAR31ttHnbLK5IZPA6p586hw4d6u06RCRM1Jbs5rDLDkB2/GiLq+k/Y1JiKPJlEX1srhstoClinXMKNzk5OVx55ZU8//zztLXpXyciEtDa4cNdtz84DHzEIOlMDBAb4aQxajTpnQtoasSUiGXOKdxs3bqVqVOn8p3vfIfU1FTuvvtu1q1b19u1icgAU1DRwChKKRpEw8CPF5WWQ+qxuW7KqnZYXI3I4HVO4SY/P59HH32U0tJSli5dSkVFBZdccgl5eXk8+uijVFWpM53IYLSzrIHRtjKKHMeGgQ+SkVKdxqTGE+0JLDVRenS3xdWIDF7n1dPP4XDwqU99ij/96U/8/Oc/58CBAyxcuJCMjAxuv/12ysu1vorIYLKztJ4s22HKHYE+N4Ot5WZsSgxGcDh4obXFiAxi5xVuNmzYwNe//nXS0tJ49NFHWbhwIQcOHODdd9+ltLSUm266qbfqFJEBYGdpLS5nFaZhEOMYwlD3UKtL6le5qTG0eZIAKGuttrgakcHLcS4HPfrooyxdupQ9e/Zw/fXX89xzz3H99ddjswWy0siRI/ntb3/LuHHjerVYEQldHV4/jUeKqIwzARgRNxLDMCyuqn/lJEdT15EJHKDU22R1OSKD1jmFm6eeeoovf/nLfOlLXyI1tfsJurKysliyZMl5FSciA8e+ykZGmIc/XlNqkPW3AYhw2vFFTgBWUmuYtHQ0M8QVZXVZIoPOOYWbFStWkJWVFWyp6WSaJiUlJWRlZeFyubjjjjt6pUgRCX07yxrIMUqDa0oNtv42nWJSJhPj89Not1FWuY2cjNlWlyQy6JxTn5vRo0dTXX3y/eSamhpGjhx53kWJyMCzs7Se0cbHw8AHy4KZJxqdlvjxApoVG60tRmSQOqdwY5pmt9ubmpqIiIg4r4JEZGDaUdZAjq3suAn8BmfLzdiUmI+Hg1drOLiIFXp0W2rBggUAGIbBgw8+yJAhQ4Kv+Xw+PvroI6ZMmdKrBYpI6PP5TQrK60mxl1FjD4yQGqzhJjc1BpsnFqimtL7Q6nJEBqUehZvNmzcDgZab7du343K5gq+5XC4mT57MwoULe7dCEQl5h6qbieyopTG2HYCkyGFEOQdnR9qRw6Lo8CQD1ZS0VFpdjsig1KNw89577wHwpS99if/93/8lNja2T4oSkYFlZ1k9Y23HjZQapP1tAJx2Gw73aGAX5RoOLmKJc+pzs3TpUgUbEQnSSKmu4hKmAFBuB1prLa1FZDA665abW265hWXLlhEbG8stt9xy2n1feeWV8y5MRAaOHaX1zDMOs32QLph5otz0cbxfAnV2O83l24gadbnVJYkMKmcdbuLi4oKzjcbFxfVZQSIysJimyc6yBu6zlfI3tdwAMCk9hahCg2a7SWn5esYq3Ij0q7MON0uXLu32zyIyuB2ubaW+1cMY92GKnYF/+Az2cJObGkuUx02zvY3DVbsYa3VBIoPMOfW5aW1tpaWlJfi8qKiIxx57jLfffrvXChORgWFnWQMJNIC9mWabDQODjJgMq8uyVHpcBE5fIOgV1RyyuBqRweecws1NN93Ec889B0BdXR0XXnghv/zlL7npppt46qmnerVAEQltO8vqGWOUUnKsv01aVBpuu9viqqxlGAaR9jQAKto0HFykv51TuNm0aROXXnopAH/5y19ITU2lqKiI5557jscff7xXCxSR0LazrIExtsPBkVKZsZkWVxQaYmMCN6OO0AYdzRZXIzK4nFO4aWlpISYmBoC3336bW265BZvNxqxZsygqKurVAkUktO0orWeMcZhiR6DlJismy+KKQsPIpHEAlDkcUL3P4mpEBpdzCjc5OTm89tprlJSU8M9//pO5c+cCUFlZ2aP5b1avXs2NN95Ieno6hmHw2muvnXb/lStXYhjGSY/du7V+i4gVKhvbqGxsZ6zt49tSCjcBk9NGAVDqsEP1XourERlczincPPjggyxcuJDs7GxmzpzJ7NmzgUArztSpU8/6fZqbm5k8eTK/+c1venT+PXv2UF5eHnyMGTOmR8eLSO/YWdYAwDh7KcXHwo1uSwXMysoBoMFu52jpVourERlcerT8QqdPf/rTXHLJJZSXlzN58uTg9jlz5vCpT33qrN9n3rx5zJs3r8fnT05OJj4+vsfHiUjv2llaz1AaiDfrKXYEblWr5SYgLTaOCJ+TNruHg+XbSbS6IJFB5JzCDUBqaiqpqaldtl144YXnXdDZmDp1Km1tbUyYMIH/+q//4sorrzzlvu3t7bS3twefNzQ09EeJIoPCzrIGxtlKqLfZaLQHGoIH+zDw40UxlDYqqWhUX0SR/nRO4aa5uZmHH36Yd955h8rKSvx+f5fXDx482CvFnSgtLY1nnnmG6dOn097ezh/+8AfmzJnDypUrueyyy7o9ZvHixTz00EN9Uo/IYLejrJ5rjOLgLankIclEOiItrip0DI3I5KinkipfLXg7wOGyuiSRQeGcws1XvvIVVq1axW233UZaWlpwWYa+lpubS25ubvD57NmzKSkp4ZFHHjlluFm0aBELFiwIPm9oaCAzU30CRM5XfYuHkppWxjuKNFLqFDKG5rK/ciPFTjvUHITkcVaXJDIonFO4+cc//sEbb7zBxRdf3Nv19NisWbN4/vnnT/m62+3G7R7cE4qJ9IWd5fUATHYe5h0tmNmt/OQcVlZCkdOBWbUbQ+FGpF+c02ipoUOHkpCQ0Nu1nJPNmzeTlpZmdRkig86usgYceBlpllDcOYFfjFpFj3dBRmAivyKng6bSXRZXIzJ4nFPLzU9+8hMefPBB/u///o8hQ4ac88mbmprYv39/8PmhQ4fYsmULCQkJZGVlsWjRIkpLS4NLPTz22GNkZ2eTl5dHR0cHzz//PMuXL2f58uXnXIOInJtd5Q2MNspw4qHYFWgdzYrVbanj5QwdCUCVw0F16TZiLK5HZLA4p3Dzy1/+kgMHDpCSkkJ2djbOY/9q67Rp06azep8NGzZ0GenU2TfmjjvuYNmyZZSXl1NcXBx8vaOjg4ULF1JaWkpkZCR5eXm88cYbXH/99edyGSJyHgrKGxlvBL6fJU4X4FefmxPEumKJNCNoNdoor9/PSKsLEhkkzinc3Hzzzb1y8iuuuALTNE/5+rJly7o8v//++7n//vt75dwicu46vH72VzZys62IBptBrREYManbUidLcKZR6j1EjecI+H1gs1tdkkjYO6dw88Mf/rC36xCRAeRAVRMen8nEiBJKHIGW22GRwxjiPPfb1OFqeNwYSo8e4rATqCuChFFWlyQS9s6pQzFAXV0dv//971m0aBE1NTVA4HZUaWlprxUnIqGpoLwBMJlg+3iOG92S6t6EpMAyDEVOJ94KdSoW6Q/nFG62bdvG2LFj+fnPf84jjzxCXV0dAK+++iqLFi3qzfpEJATtrmgkjRri/XUUOwMT0+mWVPcmJo8GoMjhoP7QZourERkczincLFiwgDvvvJN9+/YRERER3D5v3jxWr17da8WJSGgqKG9gku0AAMUxgVWTNFKqe9nx2QAUOp20lW23thiRQeKcws369eu5++67T9o+fPhwKioqzrsoEQltBeUNTLYFllkpcQf62SjcdK/zdl2j3UZr3W6LqxEZHM4p3ERERHS7AOWePXtISko676JEJHRVNrZR3dTB5M6WG8MDqM/NqUQ4IoizDwOgxncEPK0WVyQS/s4p3Nx00038+Mc/xuMJ/FAzDIPi4mIeeOABbr311l4tUERCS0F5IwZ+JtsO0WwYHPW2AOpzczojYscAcNDpgKo9FlcjEv7OKdw88sgjVFVVkZycTGtrK5dffjk5OTnExMTw05/+tLdrFJEQsru8gZFGBdG0UBIRBUBCRAIxLs2/eyoTkwML/u53OWkr3WZxNSLh75zmuYmNjeX999/nvffeY+PGjfj9fqZNm8bVV1/d2/WJSIgpKG9gkhHob1OcNAqoU6vNGeQljYU9sM/lpL5wKxEXWF2RSHjrcbjx+/0sW7aMV155hcLCQgzDYOTIkaSmpmKaJoZh9EWdIhIiCsob+Vxnf5vYFGiuU3+bMxgzNHBbar/Tie/IDourEQl/PbotZZomn/zkJ/nKV75CaWkpEydOJC8vj6KiIu68804+9alP9VWdIhIC2r0+DlQ1MalzpFREJACZsWq5OZ2RcSMxMGiw2+lo2Gd1OSJhr0ctN8uWLWP16tW88847XRa8BHj33Xe5+eabee6557j99tt7tUgRCQ37jjSB30OerRCAIrMD0EipM3Hb3SS40jjaUUaZrZnspiqI1shSkb7So5abl156ie9973snBRuAq666igceeIAXXnih14oTkdBSUN7AWOMwEXjAHUdJaxUAI2JHWFxZ6Bsdd+zWlMuJeWSnxdWIhLcehZtt27Zx3XXXnfL1efPmsXXr1vMuSkRC0+6KxuAtqZb0yVQeCzfqUHxmk1ICI6YOuJw0FW+xthiRMNejcFNTU0NKSsopX09JSaG2tva8ixKR0FRQ3sBkI9CZuDApsGZSQkQCce44K8saEHITP+5U3FK0yeJqRMJbj8KNz+fD4Th1Nx273Y7X6z3vokQk9Jim2WXZhcLYwKy72bHZFlY1cIyJD4SbfS4n9iqtMSXSl3rUodg0Te68807cbne3r7e3t/dKUSISeo40tNPa0sRYdwkAhcf+oZMdl21hVQPHiNgROHDSavNQ31HKME8rOCOtLkskLPUo3Nxxxx1n3EcjpUTCU0F5AxOMIhyGH6JTKGw/Cqjl5mw5bA6GR42hqHkXu112Rh/ZBRnTrS5LJCz1KNwsXbq0r+oQkRC3q7whuFgm6dMobCgCFG56In/YBIqad1HgdjGvbAs2hRuRPnFOa0uJyOBz/Egpf/o0ChsKAd2W6okL0ycBsMvlorFwo8XViIQvhRsROSvHrylVmTSSVm8rDsNBRkyGxZUNHHnDJgBQ4HbhK9e0GSJ9ReFGRM6ozeOjquoIo23lABwaEhj6nRGTgdPmtLK0AWVU/ChsOGiy2ahvPgg+jS4V6QsKNyJyRnuPNJJ/rNXGHJqtzsTnyGlzkuQeCcAeJ1C919qCRMKUwo2InFHgltQhAIz0aRTWFwLqb3MuxsaPA6DA5QTdmhLpEwo3InJGBeWN5B/rTEz61I87E6vlpscuHB7oVLzT7cZTusXaYkTClMKNiJxRQXkD+UZh4EnaZA7UBYaEj4ofZV1RA9Ss4VMA2Ol20Vqy2dpiRMKUwo2InJZpmhwuL2OErRKAhsRRHGk5AsDo+NFWljYg5cTnYDedNNlslNXtBtO0uiSRsKNwIyKnVVbfRlZHoKXGjM/mQHs1AClDUoh1xVpZ2oDksDlIcOYAUODwQm2htQWJhCGFGxE5rYKyBiYeGyllpE9hf91+AHKG5lhZ1oA2Jj4fgK1utzoVi/QBhRsROa2C8gbybYWBJ2mT2V8bCDedq1xLz12cMQ2A7W4XZvk2i6sRCT8KNyJyWrsrGsk/NgyctMkft9zEq+XmXF0z6gIA9rucVBdvsLgakfCjcCMip1VYVsEoW0XgSZpuS/WGtJgUIvwx+A2DvTW71KlYpJcp3IjIKTW1e4mp3QWALyaDozaoaavBwGBUnIaBn48k13gACuzt0FBqcTUi4UXhRkROaXd5A3nHbknZh08Jzm+TEZNBpCPSytIGvPGJkwHY6napU7FIL1O4EZFT2lXeQL6ts7/NFPbV7QPU36Y3XJY9A4Dtbjf+w5ssrkYkvCjciMgp7Sw9bmbi9Cnsq1W46S1Xj5qKzTQ46rBzoGSd1eWIhBWFGxE5pYNlRxhtlAWepE1md81uAMYljLOwqvAQ5YokxpcMwK76PRZXIxJeFG5EpFsenx975U5shok3Kg3PkKHsrd0LwPjE8RZXFx6SIycCsMvWAQ3lFlcjEj4UbkSkWweqmhhnBjoQ24dP5mDdQTx+DzHOGDKiMyyuLjxMSpkOwOYIzVQs0psUbkSkW7vKPp6Z2EifSkFNAQDjEsdhGIaFlYWPa0bPAmCvy0nTYfW7EektCjci0q1dZR8PAydtMgVHj4Ub9bfpNTMzRzHE48ZnGGwo+dDqckTChsKNiHRrb2kVY4xjk8ulTQ623IxPUH+b3uKw2xhqZgGwvemQxdWIhA+FGxE5iWma+Mt34DD8eCKT8EenBEdKTUicYHF14SU19kIAdto90FRpcTUi4UHhRkROUlrXSrYnMKeNLX0yRY3FtHpbibBHkB2bbW1xYWZm5mwAtka48ZVttrgakfBgabhZvXo1N954I+np6RiGwWuvvXbGY1atWsX06dOJiIhg1KhRPP30031fqMggs6usIbgSuH341GB/m7EJY7Hb7FaWFnbm5kzB5TdostnYc2il1eWIhAVLw01zczOTJ0/mN7/5zVntf+jQIa6//nouvfRSNm/ezPe+9z3uu+8+li9f3seVigwuO8oamGj7uDPx1qrAMOX8xHwLqwpPo5JiSWyPB2Bd2QZrixEJEw4rTz5v3jzmzZt31vs//fTTZGVl8dhjjwEwfvx4NmzYwCOPPMKtt97aR1WKDD67Siq51zgceJI2hS0HngdgavJUC6sKT4ZhkGgfQznr2NFeZnU5ImFhQPW5Wbt2LXPnzu2y7dprr2XDhg14PJ5uj2lvb6ehoaHLQ0ROzTRNWg9vx2n48LqH0jIkgT01geUBpiRPsba4MJWVdBkAOxx+aD5qcTUiA9+ACjcVFRWkpKR02ZaSkoLX66W6urrbYxYvXkxcXFzwkZmZ2R+ligxYh2tbyWoPdCY2hk9hx9Gd+EwfqVGppEalWlxdeLo85zJspkmp00Fl4SqryxEZ8AZUuAFOmhnVNM1ut3datGgR9fX1wUdJSUmf1ygykG07XM/Ezs7E6VPYXBkYwTMlaYqFVYW3mdnppHQ4AVh/6F2LqxEZ+AZUuElNTaWioqLLtsrKShwOB4mJid0e43a7iY2N7fIQkVPberiOvGPLLpA2mS1VWwDdkupLidFuEjyBVukNVdstrkZk4BtQ4Wb27NmsWLGiy7a3336bGTNm4HQ6LapKJLzsKK5inFEMgD91UnCklMJN30qJCKwQvtOrPjci58vScNPU1MSWLVvYsmULEBjqvWXLFoqLAz9YFy1axO233x7cf/78+RQVFbFgwQIKCgp49tlnWbJkCQsXLrSifJGw4/ObtJftwm148bniOGjz09jRSKQjkrFDx1pdXlgbk3UtAPuc0NqgUVMi58PScLNhwwamTp3K1KmB4aULFixg6tSpPPjggwCUl5cHgw7AyJEjefPNN1m5ciVTpkzhJz/5CY8//riGgYv0koNVTYz27QfASJ/MlmOtNhOHTcRpU+toX5o1ZioJXhOvYbB939+tLkdkQLN0npsrrrgi2CG4O8uWLTtp2+WXX86mTZv6sCqRwWvr4XryjUIgsOxCZ2fiyUmTLaxqcMgfHk9GWyQ10W18WPxvLpz+/1ldksiANaD63IhI39p2uO64mYmnBPvbaPK+vhfhtJPozwBgS91+i6sRGdgUbkQkaHtJDeONIgCOJmRT1BD486SkSVaWNWikxl4AQAGN+Pw+i6sRGbgUbkQEgA6vn47y3UQYHvzOaLZ66wHIic8hzh1ncXWDw7ic64ny+2myGeyp2Gh1OSIDlsKNiACwu6KBceYBAIz0ScHOxOpv038m5oxmQlugH+JH6lQscs4UbkQEgE1FteQf629jpE3R5H0WGJ0UTVprPAAflK2zthiRAUzhRkQA2FhcFww3HSn57KzeCagzcX+y2QyS7LkAbGsvx+v3WlyRyMCkcCMiAGwtrA4OA98VFUuHv4OEiASyYrKsLWyQSUu+hFifj1bDz66ju6wuR2RAUrgRESob2ohs2E+k0YHpimJLezUQ6G9zqkVppW8kj53FjLZ2ANYd/rfF1YgMTAo3IsKm4lom2Q4CYKRNZUu11pOyyoQxoxnXagfgw6KV1hYjMkAp3IgIm4rrmGgE+tuY6VPYUrkFUH8bK6TERhDfkQ7Alvr9eHweiysSGXgUbkSEjUUft9wcHpbN0bajOG1OJiROsLiywWnIkEkk+Hy04w3OEi0iZ0/hRmSQ6/D62V16lPFGYJHaLY7Aj4UJiRNw291WljZoOTOmMbu1DYAPyj6wuBqRgUfhRmSQ21lWT7avCLfhwYyIY3NLKQBTkqZYW9gglpw7i4tbWgH44PBqi6sRGXgUbkQGuU3FdR93Jk6fqsn7QsD4MTmMaQm0mhXU7qW6tdriikQGFoUbkUFuU3EtE41AuGlIzWN/bWBFaoUb60S5HdTZc5jQHhgSvqZsjcUViQwsCjcig9zmolomHZuZeHtMAiYmGdEZDIscZnFlg1vT0DwuPtbv5v3D71tcjcjAonAjMoiV17dytL6BXKMEgM10ABoCHgqcmdO49Fi/mzXla/D5fRZXJDJwKNyIDGKbiuoYbxTjNHwwZBhbGgK3p3RLynqp42cxsb2DaJ+f+vZ6dh7daXVJIgOGwo3IIBaYmfgAAN60yWyr3gYo3ISC0SNzqDPjmN12bEh4qYaEi5wthRuRQWxTcS3TbPsA2J+SQ6u3lWhnNKPjRltcmTgcdordY7jk2K2p90vV70bkbCnciAxSbR4fO0sbmGYEws3WyCgAJg6biN1mt7I0OaYlMT/YqXh79Xbq2uqsLUhkgFC4ERmkdpbVE+urJctWhYnBNn8TAJOSJllcmXSKyJpGis/HiA4wMTUkXOQsKdyIDFLrC2uZZtsLgJE8nm01uwGYnDTZyrLkOMMnzAbgspZGANaWr7WyHJEBQ+FGZJDaUFjDNFtgwr669CkUNhQCgdtSEhpSM3OoI4ZL2gL9btaWrcU0TYurEgl9Cjcig5Dfb7KhqJapxzoTbxuaCkB2bDbxEfEWVibHM2w2DkeMZVpbOw5sHGk5wqH6Q1aXJRLyFG5EBqEDVU00tbQy6diyC9scge3qbxN62pImEWGajPEMAXRrSuRsKNyIDELrC2sZbxQTaXRARDzbmg8D6m8TioaMmAbA9KYWIHBrSkROT+FGZBDaUFjD9GOdif3DZ7C9egeglptQlJF3EQDzmisAWFexDo/PY2VJIiFP4UZkEFpfVBOcvO9gai5NniYiHZHkxOdYXJmcKDZ1NA1Ek+9pI8YeTau3la1VW60uSySkKdyIDDIV9W2U1LQw01YAwLaoWADyh+XjsDmsLE26YxgcicrFBuT4EgE0343IGSjciAwyG4pqGGEcIcWoA7uLrf7AHCqThumWVKhqT5sOwIT6dgA2HNlgZTkiIU/hRmSQ2VBYG2y1Yfh0th3dBai/TSiLH3sJAJfXFwOwo3oH7b52K0sSCWkKNyKDzPrCmmC4acy8gAN1gVXBFW5CV3reZQDM8lUQ7xyKx+9he9V2i6sSCV0KNyKDSGObh4LyBmbaAkstbB+ahonJ8OjhDIscZnF1ciq2qKGUOEZgACNJAmDjkY3WFiUSwhRuRAaRTcV1pFNFhlENNgfbbD5ArTYDQW3iVABGNQSGgW+q3GRlOSIhTeFGZBD56OBRZhrH+tukT2VbTeDPmrwv9DmzA4tozqgtB2BL5Ra8fq+VJYmELIUbkUFkzYGjwf42ZtZstlVvAxRuBoLhEy8H4Kq2Q0Q7Y2jxtrCnZo/FVYmEJoUbkUGisc3D9tL6YLgpShlHfXs9LpuL3KG5FlcnZxI7fBy1RhxDDA+jnRmAbk2JnIrCjcggsb6whjTzCCNslWDY2eYKTNg3IXECTrvT4urkjAyD0uiJAGQ2GQAaMSVyCgo3IoPE2gNHudR27Jdh5oVsqw8sv6BbUgOHJ30GAONqjwAEbyuKSFcKNyKDxJrjw82oK4PrE2mk1MARP+EqAK5u2IeBQWlTKUdbj1pclUjoUbgRGQTqWjrYXV7HxbbA6t8t2ReztzawKrjCzcCRlXcRjWYkw2liuDsFgO3VujUlciKFG5FB4MODNUzkIHFGC0TEsdPpwG/6SR6STGpUqtXlyVmyO5zsHxK4jZjV4QZgW5VuTYmcSOFGZBD48OBRLrUd+yU48jK21gRacKYkTbGuKDknrcMvAmBcXS2glhuR7lgebp588klGjhxJREQE06dP59///vcp9125ciWGYZz02L17dz9WLDLwrNpbxSX2QKBh9FVsrQz0t1Fn4oEnIf8aAK5oOgQEFtH0m34rSxIJOZaGm5dffplvfetbfP/732fz5s1ceumlzJs3j+Li4tMet2fPHsrLy4OPMWPG9FPFIgNPYXUzldXVTDMCo6PMkVcEOxNPTla4GWhy8i+k1oxhYkczLsNJk6eJwvpCq8sSCSmWhptHH32Uu+66i6985SuMHz+exx57jMzMTJ566qnTHpecnExqamrwYbfb+6likYFn5Z5KLrFtx2n4YOhIip12attrcdqcjE8Yb3V50kMOh4P9UVNwANlmNKAh4SInsizcdHR0sHHjRubOndtl+9y5c1mzZs1pj506dSppaWnMmTOH995777T7tre309DQ0OUhMpi8t6eKa+zHZrLNnRdstclLzMNld1lYmZyrpqwrAZjQ1AhoMj+RE1kWbqqrq/H5fKSkpHTZnpKSQkVFRbfHpKWl8cwzz7B8+XJeeeUVcnNzmTNnDqtXrz7leRYvXkxcXFzwkZmZ2avXIRLK2jw+1h2s4krb5sCG3HnqbxMGkqbeCMAlzYFFNNWpWKQrh9UFGIbR5blpmidt65Sbm0tu7sdr4MyePZuSkhIeeeQRLrvssm6PWbRoEQsWLAg+b2hoUMCRQWPtwaNM8O0h0dGIGRGHkTWbrdsfB9TfZiAbP2YM28lhcnugU/He2r20eluJdERaXJlIaLCs5WbYsGHY7faTWmkqKytPas05nVmzZrFv375Tvu52u4mNje3yEBks3t55hKuP3ZIycq6h2d/BvjotuzDQ2W0GRYmXkeLzMdRvx2f6KDhaYHVZIiHDsnDjcrmYPn06K1as6LJ9xYoVXHTRRWf9Pps3byYtLa23yxMZ8Hx+kxW7Krja9nF/m+3V2/GbftKj0kkekmxtgXJe3HnXYwCTW5sB3ZoSOZ6lt6UWLFjAbbfdxowZM5g9ezbPPPMMxcXFzJ8/HwjcUiotLeW5554D4LHHHiM7O5u8vDw6Ojp4/vnnWb58OcuXL7fyMkRC0vrCGqKaixnjLsW0OTByrmbr3pcBtdqEgykzLqVsVQKT29tYGRUR7CguIhaHm89+9rMcPXqUH//4x5SXl5Ofn8+bb77JiBEjACgvL+8y501HRwcLFy6ktLSUyMhI8vLyeOONN7j++uutugSRkPXWjgqusW0EwBhxEUTGa36bMJIUG8FfIy9lUvtbgFpuRI5nmKZpWl1Ef2poaCAuLo76+nr1v5Gw5febXPTwuzzd9p9MsR2A6x/BN+PLXPrHS2n0NPLHT/yRvGF5Vpcp5+nPf/0r12+5g9kjMjANg3f/412ShiRZXZZIn+jJ72/Ll18Qkd63uaQOR2MJU2wHMA0bjP8ke2v30uhpJMoZRW5C7pnfRELejIvmUOlLZrTHA2gyP5FOCjciYejVzYf5hO1DAIwRF0NMCusr1gMwLXkaDpvls0BILxiZFM2aIVcxqb0D0GR+Ip0UbkTCTLvXx9+3lfMJeyDckH8LABuObABgRuoMq0qTPuCd9Hny246Fm/KPLK5GJDQo3IiEmfd2VxHXWsIk2yFMww7jP4nf9LPxSKBz8QUpF1hcofSmqy+6gLbWkQBsP1qAz++zuCIR6ynciISZwC2pwL/gjZGXQdQw9tXuo6GjgSGOIYxP1GKZ4WR4fCQViZ8h0u+nFR8Hq3dZXZKI5RRuRMLI0aZ23t19hJvsHwQ25H0KINjfZmrKVPW3CUMTL72VnPbAwNctm5+1uBoR6ynciISRv2w8zDj/QXJth8ERAXk3A/BRRaAlZ0aK+tuEozkT0jA6RgGw5eAK8HktrkjEWgo3ImHC7zd5aV0xn7avCmwYfyNExOHxefjoWEfTi9LPfmkTGTicdhvZo28FoMDhwb/zNWsLErGYwo1ImFhz4ChlR+u52b4msGHK5wHYXLmZVm8riRGJjEsYZ2GF0pfuviQwU/t+p5PSdx6GwTU/q0gXCjciYeLFdUXMsW0izmiG2OEw8nIA3i97H4CLh1+MzdBXPlxlxaWQ4EjHNAz2eg7TUfAPq0sSsYx+0omEgcrGNt7eeYRP21cHNkz+HNjsALxfeizcpF9sVXnST67MDnzGGyLc1L71M7XeyKClcCMSBl74sJhkfxVX2I+tDD05cEvqSPMR9tXuw8BQf5tBYNbwCwFYFxFJSsN2GgretbgiEWso3IgMcG0eHy98VMQXHf/Cjj9wO2pYDgAflAWGhE8cNpH4iHgLq5T+0Dkabq/bSZ3NRtWbP7W4IhFrKNyIDHCvby2jsamJzzveC2y48P8Lvvavon8BcFnGZVaUJv1sWOQwRseNBuD9iCGMbtpI4Zb3LK5KpP8p3IgMYKZp8uz7h7jB9iHxNEJcJoy9DoCGjgbWlq8F4Jrsa6wsU/pRZ5B9LS6wJEPtWz/DVN8bGWQUbkQGsLUHjrK7ooGvOI+NjJnxZbAHZiBeVbIKr9/L6LjRjIobZWGV0p86w01BtI8O02Bq2zo+XLPS2qJE+pnCjcgA9uwHh7jKtpnxRhG4omH6ncHX3i56G1CrzWAzJXkKMa4YGrxNvJlyCQBt7/6Cdq8W1JTBQ+FGZIDaX9nIO7uPcK/jtcCGC+6CIQkA1LTV8P7hwBDwa0dca1GFYgWHzcEl6YFQs2/CJAAu967l1bfV90YGD4UbkQHqyZUHuMjYwVTb/sA6UrPvCb72xsE38Jpe8hLzyBmaY2GVYoU5I+YAsKJ6A4dTrsRmmER+9L9UN7VbXJlI/1C4ERmASmpaeH3LYR5wvBTYMP1OiE4GAp2MX9v/GgA359xsSX1irSsyryDGGUN5czmlF38agOv5gJfeft/iykT6h8KNyAD0u38f5GZjNRNtheCOhUsXBl/bVr2NvbV7cdlczBs5z7oixTJuu5u52XMBeKNxL7UpF+E0fMRv+S2VDW0WVyfS9xRuRAaYysY2Xl+/j/sdLwc2XPafEJ0UfP0Pu/4AwPWjrifOHWdFiRICbhh1AwD/LPwntqvuBeA/jHf5v3+tt7IskX6hcCMywDzx7n6+yUskG3WYQ0fCzLuDr5U2lbKiaAUAt024zaoSJQRMT5lOTnwOLd4W/tJRTmPiJCIMD9Fbfs8Rtd5ImFO4ERlASmpa2L/+Lb7k+CcAxiceAYc7+PqyHcvwm35mpc1i7NCxVpUpIcAwDO7MuxOAFwpewH3ltwH4gvE2v//XFusKE+kHCjciA8gT/9zCYtvTgSfT74Scq4OvHW48zF/2/QWAr078qgXVSai5fuT1JEcmU9VaxZ9tLbTE5RBrtODevIyyularyxPpMwo3IgPE7ooG8nb9kixbFR3RGTD3v7u8/uSWJ/H6vcxOm82FaRdaVKWEEqfdyd2TA7ctn9r2NJ5Lvw7AHbY3+O07O60sTaRPKdyIDACmafLKX57nNntgIUzXLU+AOyb4+oaKDfzt4N8AuG/afZbUKKHpljG3kBOfQ317Pb/xlNEelU6S0QBbnqekpsXq8kT6hMKNyADwz037uL3qlwA0TrwTRl0RfK3D18FDax8C4NNjP03+sHwLKpRQ5bA5uP+C+wH4494/sWV6YN6bu21/VeuNhC2FG5EQ19Tupe2NRWQY1dRFDCfmhp92ef2Zbc9Q2FBIYkQi35r2LWuKlJA2O302/zH2PwD4wdEPqYlOJ92oIWbrEoqPqvVGwo/CjUiI+9Mfl3GzP3A7KvI/fgvu6OBr6yvW87vtvwPggZkPaF4bOaXvzPgOw6OHU95SwU9z8jGBr9n/ypK3N1hdmkivU7gRCWGrt+1j3sFAS03ZuDtxj740+FpNWw0PrH4Av+nn5pybuS77OqvKlAEgyhnFw5c+jMPm4O363SxJDYycGrXr1+ypaLS6PJFepXAjEqIqG9uof/U/STNqOOrOIP2WxcHXOnwdfPu9b1PZWsmouFEsunCRhZXKQDEleUqw/81vIr2sj3Bzm20FL72yHNM0La5OpPco3IiEoA6vn98veYobzffwYxD92WfANQQIjJx6aO1DbKrcRLQzmkeveJQhziEWVywDxedyP8cNo27Ah5/vpA2nwmnj/1X8Dyt3FFldmkivUbgRCTGmabJ4+Rruqn0MgIapd+MedXHw9d9t/x2vH3gdu2HnkcsfYXT8aIsqlYHIMAwenP0guUNzqcXL11JTSbeX0vLaAlo6vFaXJ9IrFG5EQohpmvz077uYseMhUow6mmNHEX/9j4Kv/2HXH/j15l8D8N0Lv8vFwy8+xTuJnFqkI5LfzPkNSZFJHHTaWZicxLW+d1jzfw9aXZpIr1C4EQkRPr/JT98ooOXDJXzCvg6f4SDqs0vAGQnAn/b8iV+s/wUAX5v8Nf7fuP9nZbkywKVGpfLrOb8m0hHJmiER/PewBOaUPkHJ3xeD+t/IAKdwIxICGts83P2HDaz94F0edDwHgP2ah2D4NEzT5OmtT/OTD38CwJfyv8TXJn/NynIlTOQl5vHwpQ9jYLA8JppfJMSTseFh2v94JzRVWV2eyDlTuBGxkGma/HNnBXN/tZpdBbtY6nqECMMDY+bCrK/j8Xl4aO1DPLHlCQDuyr+Lb0/7NoZhWFy5hIursq7ioYsCM1w/HxfLo0Pjce15DfPX02DFg1BXYnGFIj1nmINs/F9DQwNxcXHU19cTGxtrdTkySLV0eHl75xGWvH+I7aX1ZBpHeDniYdLNI5A8Ab78FqXeJhauXMiOozuwGTYWXbiIz437nNWlS5h6effL/PdHgcVYr2qAXx4txgGAEVjuY8rnYdwNwVF7Iv2tJ7+/FW5E+onfb7L24FGWbzrMP3dU0NzhA+Aa13Yecz1NlLcWho7EvONvvFGzlZ999DMaOxqJdcWy+NLFXJZxmcVXIOHuT3v+xH9/+FNM/MQ1p/B4q5dpjZs/3sEVA3k3w5QvQNYsUAui9COFm9NQuJH+VtnQxvMfFrF8Uymlda3B7bPj6/lR9CvkVq8IbEiZSPktT/Lj7U/xfun7AEwaNon/ufx/SI9Ot6J0GYTeLX6X76z8T7xmB35PLLOMW3gyqxX3zj9B3XFz4QzLhSu/BxNuUsiRfqFwcxoKN9JfKhvbeHrlQV74qIh2rx+AoRHwnRGHuNH7NrGlqzEwAYOWC77E/6WNYmnBH2j1tuK0OZk/eT5fyv8STpvT2guRQWdPzR6+9va3qWoP9LdxtU/hRxcv5MaoJtjyIux6DTqaAjunTYE5P4DRcxRypE8p3JyGwo30teqmdn676gB/+LCINk8g1NyQ3sS3Ej9kdNnfMJo/HoXSOnoOr+VezDOFf6e6tRqAacnT+OFFP2RU3ChL6hcBaPG08IPV/8PbJcvBMDFNg1T7bL5z4d3MG5EDa38Da5/4OOSMuASu/iFkXmht4RK2FG5OQ+FG+kplQxu/f/8Qf1hbRKvHRwTtzE/awZ2Rq4mvXP/xjtEpHMq7kb/FxvLnkn9R114HQGZMJt+c9k3mjpir0VASMjaW7eT+d39Ope/jvjcRvjFcnnozXx13EWP3LMHYsAR87YEXx14Hs74G2ZeBTQNypfcMqHDz5JNP8j//8z+Ul5eTl5fHY489xqWXXnrK/VetWsWCBQvYuXMn6enp3H///cyfP/+sz6dwI73tQFUTSz84xJ82HKbD62OKcYCvxq1jrm8VTk9gteUOw8bW0RfzYcpo/t1WRkHN7uDxw6OHc0feHXx6zKdx2nULSkLT3wrW86sNT1Pp24BhBFok/Z5YbE2zuWTIdL7u+wd5lX/HZgY6yjN0JIz7BIy+KtCa446xsHoJBwMm3Lz88svcdtttPPnkk1x88cX89re/5fe//z27du0iKyvrpP0PHTpEfn4+X/3qV7n77rv54IMP+PrXv85LL73ErbfeelbnVLiR8+X3m+yuaGTNgWr+vq2c3SVHmGHbyyW27XzKtZ5Ys5Iip4MCl4uCmEQK4pLY7W2grfNftoDdsHNR+kXcnHMzc7LmYLfZLbwikbO3s7KYx9f9gXXVb+A1AuHdNG34msYytCGbu1oP8BnbGmKM1i7H+eOysKVMgKRcSBgNiaMD/x+Tqr46clYGTLiZOXMm06ZN46mnngpuGz9+PDfffDOLFy8+af/vfve7vP766xQUFAS3zZ8/n61bt7J27dqzOqfCjXSnvaOD2toqqmoPU1NfTl3TEeqbj9Lc3khLRzPtHc20eVpo6mih1dOKz/TgsrUSbTThtrXQYYMKu51ip4NKh6PbcyRGJDIzbSaz0mZxeeblJEQk9PNVivSeDl8H/zz0Nkt3PM+++p3B7aZph9bhZLW6mOKt42LfYUaZtUT7TSJNP07TxGWCyzSxA177ENpisuiIH4WZMBpb4mhcKWOITBmLLTpJwUeCevL7u/ufwv2go6ODjRs38sADD3TZPnfuXNasWdPtMWvXrmXu3Lldtl177bUsWbIEj8eD03lyk357ezvt7R//i7mhoaEXqj9ZRXUJD7/6pS7bzNM8+3jrqbKl2c2fun83w+zuXU519q5/Mk5Z2emrO/69Tnnurv/XlXGavx2z262n/Bvs8T6mn3Y8tNl8tBp+WmwmzTaD1tP1D7AB7mOPLgwg6qTdY12xjEsYx/iE8YxPDDxGxo5UXxoJGy67ixtzbuDGnBs4WHeQvx/8O28eepPSplIYUkzJECgB/kYEkNbte9hNE6dp4jSbcPm24qragqvSxLnLDIQf04Zh2rFjx2basRkODMOBDQO7YSP4P8OGYRq9GoR695s6+L73kfZIFn/5dcvOb1m4qa6uxufzkZKS0mV7SkoKFRUV3R5TUVHR7f5er5fq6mrS0k7+Ai1evJiHHnqo9wo/hYbmo7zjOtLn55HednKgifCbRPkh0rThNm24sOMy7DgNB5EOF1EONzHuSCKcUbijknDHpOEekkRSVDJZMVlkxWQR545TkJFBY1T8KO6bdh/3Tr2Xw42HWVexjoKaAkoaSyhrKqPF00Kjp4k2b2uXfzL5DAOfYdB2xjOYgPfYQwaCxGPTX1jFsnDT6cRfAKZpnvaXQnf7d7e906JFi1iwYEHweUNDA5mZmeda7inFRSdxvS/7pO3GCYn9+GfmsZqNbl89m/c5/S/PE/9OTnwP0+jufY0uz05Z2Rne+0z7n/mIE67wpL+rU78TGCftePw+doeDIe544iITiY9OYmhsCknx6aQMzSBmSAIOm+VfC5EByTAMMmMzyYw99c9Yr99Lh68Dj99Du6+dDl8HHf4OPD4PHb4O2n3tNHvaaWhuoLm2hLaWOlrbG2hvb8bjacbrbcPj8+Hze/Hjw2/68Zk+wB+Si5mfTet3OIpwWLtMh2U/xYcNG4bdbj+plaaysvKk1plOqamp3e7vcDhITEzs9hi3243bfdK9hF6Xkjicn3/5b31+HhGRgcxhc+gfENLnLJuEwOVyMX36dFasWNFl+4oVK7jooou6PWb27Nkn7f/2228zY8aMbvvbiIiIyOBj6QxLCxYs4Pe//z3PPvssBQUFfPvb36a4uDg4b82iRYu4/fbbg/vPnz+foqIiFixYQEFBAc8++yxLlixh4cKFVl2CiIiIhBhL2wY/+9nPcvToUX784x9TXl5Ofn4+b775JiNGjACgvLyc4uLi4P4jR47kzTff5Nvf/jZPPPEE6enpPP7442c9x42IiIiEP8tnKO5vmudGRERk4OnJ728t/CEiIiJhReFGREREworCjYiIiIQVhRsREREJKwo3IiIiElYUbkRERCSsKNyIiIhIWFG4ERERkbCicCMiIiJhZdAtzdo5IXNDQ4PFlYiIiMjZ6vy9fTYLKwy6cNPY2AhAZmamxZWIiIhITzU2NhIXF3fafQbd2lJ+v5+ysjJiYmIwDKNX37uhoYHMzExKSkrCct2qcL8+CP9r1PUNfOF+jbq+ga+vrtE0TRobG0lPT8dmO32vmkHXcmOz2cjIyOjTc8TGxobtf7QQ/tcH4X+Nur6BL9yvUdc38PXFNZ6pxaaTOhSLiIhIWFG4ERERkbCicNOL3G43P/zhD3G73VaX0ifC/fog/K9R1zfwhfs16voGvlC4xkHXoVhERETCm1puREREJKwo3IiIiEhYUbgRERGRsKJwIyIiImFF4aYHamtrue2224iLiyMuLo7bbruNurq60x5z5513YhhGl8esWbO67NPe3s69997LsGHDiIqK4pOf/CSHDx/uwyvpXk+vz+Px8N3vfpeJEycSFRVFeno6t99+O2VlZV32u+KKK076O/jc5z7Xx1cT8OSTTzJy5EgiIiKYPn06//73v0+7/6pVq5g+fToRERGMGjWKp59++qR9li9fzoQJE3C73UyYMIFXX321r8o/o55c3yuvvMI111xDUlISsbGxzJ49m3/+859d9lm2bNlJn5VhGLS1tfX1pZxST65x5cqV3da/e/fuLvsN1M+wu58nhmGQl5cX3CeUPsPVq1dz4403kp6ejmEYvPbaa2c8ZqB9B3t6jQPte9jT6wuZ76ApZ+26664z8/PzzTVr1phr1qwx8/PzzRtuuOG0x9xxxx3mddddZ5aXlwcfR48e7bLP/PnzzeHDh5srVqwwN23aZF555ZXm5MmTTa/X25eXc5KeXl9dXZ159dVXmy+//LK5e/duc+3atebMmTPN6dOnd9nv8ssvN7/61a92+Tuoq6vr68sx//jHP5pOp9P83e9+Z+7atcv85je/aUZFRZlFRUXd7n/w4EFzyJAh5je/+U1z165d5u9+9zvT6XSaf/nLX4L7rFmzxrTb7ebPfvYzs6CgwPzZz35mOhwO88MPP+zz6zlRT6/vm9/8pvnzn//cXLdunbl3715z0aJFptPpNDdt2hTcZ+nSpWZsbGyXz6q8vLy/LukkPb3G9957zwTMPXv2dKn/+O/SQP4M6+rqulxXSUmJmZCQYP7whz8M7hNKn+Gbb75pfv/73zeXL19uAuarr7562v0H2nfQNHt+jQPte9jT6wuV76DCzVnatWuXCXT5y1+7dq0JmLt37z7lcXfccYd50003nfL1uro60+l0mn/84x+D20pLS02bzWa+9dZbvVL72TjX6zvRunXrTKDLD+fLL7/c/OY3v9mb5Z6VCy+80Jw/f36XbePGjTMfeOCBbve///77zXHjxnXZdvfdd5uzZs0KPv/MZz5jXnfddV32ufbaa83Pfe5zvVT12evp9XVnwoQJ5kMPPRR8vnTpUjMuLq63SjxvPb3Gzh+stbW1p3zPcPoMX331VdMwDLOwsDC4LdQ+w05n84txoH0HT3Q219idUP8edupJuLH6O6jbUmdp7dq1xMXFMXPmzOC2WbNmERcXx5o1a0577MqVK0lOTmbs2LF89atfpbKyMvjaxo0b8Xg8zJ07N7gtPT2d/Pz8M75vbzqf6ztefX09hmEQHx/fZfsLL7zAsGHDyMvLY+HChcHV2ftKR0cHGzdu7PL3CjB37txTXs/atWtP2v/aa69lw4YNeDye0+7Tn58VnNv1ncjv99PY2EhCQkKX7U1NTYwYMYKMjAxuuOEGNm/e3Gt198T5XOPUqVNJS0tjzpw5vPfee11eC6fPcMmSJVx99dWMGDGiy/ZQ+Qx7aiB9B3tLqH8Pz5XV30GFm7NUUVFBcnLySduTk5OpqKg45XHz5s3jhRde4N133+WXv/wl69ev56qrrqK9vT34vi6Xi6FDh3Y5LiUl5bTv29vO9fqO19bWxgMPPMDnP//5LoulfeELX+Cll15i5cqV/OAHP2D58uXccsstvVZ7d6qrq/H5fKSkpHTZfrq/14qKim7393q9VFdXn3af/vys4Nyu70S//OUvaW5u5jOf+Uxw27hx41i2bBmvv/46L730EhEREVx88cXs27evV+s/G+dyjWlpaTzzzDMsX76cV155hdzcXObMmcPq1auD+4TLZ1heXs4//vEPvvKVr3TZHkqfYU8NpO9gbwn172FPhcp3cNCtCn6iH/3oRzz00EOn3Wf9+vUAGIZx0mumaXa7vdNnP/vZ4J/z8/OZMWMGI0aM4I033jjtL/gzve/Z6uvr6+TxePjc5z6H3+/nySef7PLaV7/61eCf8/PzGTNmDDNmzGDTpk1MmzbtbC7jnJ1Y+5mup7v9T9ze0/fsS+day0svvcSPfvQj/vrXv3YJtbNmzerS4f3iiy9m2rRp/PrXv+bxxx/vvcJ7oCfXmJubS25ubvD57NmzKSkp4ZFHHuGyyy47p/fsa+day7Jly4iPj+fmm2/usj0UP8OeGGjfwfMxkL6HZytUvoODPtzcc889Zxy5k52dzbZt2zhy5MhJr1VVVZ2UQE8nLS2NESNGBBN4amoqHR0d1NbWdmm9qays5KKLLjrr9z2V/rg+j8fDZz7zGQ4dOsS77757xiXup02bhtPpZN++fX0WboYNG4bdbj/pXwKVlZWnvJ7U1NRu93c4HCQmJp52n578N9AbzuX6Or388svcdddd/PnPf+bqq68+7b42m40LLrjAkn8xns81Hm/WrFk8//zzwefh8Bmapsmzzz7LbbfdhsvlOu2+Vn6GPTWQvoPna6B8D3uDFd/BQX9batiwYYwbN+60j4iICGbPnk19fT3r1q0LHvvRRx9RX1/foxBy9OhRSkpKSEtLA2D69Ok4nU5WrFgR3Ke8vJwdO3b0Srjp6+vrDDb79u3jX//6V/AH0Ons3LkTj8cT/DvoCy6Xi+nTp3f5ewVYsWLFKa9n9uzZJ+3/9ttvM2PGDJxO52n36Y3PqifO5fog8C/FO++8kxdffJFPfOITZzyPaZps2bKlTz+rUznXazzR5s2bu9Q/0D9DCAyX3r9/P3fdddcZz2PlZ9hTA+k7eD4G0vewN1jyHey1rsmDwHXXXWdOmjTJXLt2rbl27Vpz4sSJJw2Vzs3NNV955RXTNE2zsbHR/M53vmOuWbPGPHTokPnee++Zs2fPNocPH242NDQEj5k/f76ZkZFh/utf/zI3bdpkXnXVVZYNBe/J9Xk8HvOTn/ykmZGRYW7ZsqXLsL/29nbTNE1z//795kMPPWSuX7/ePHTokPnGG2+Y48aNM6dOndrn19c5zHbJkiXmrl27zG9961tmVFRUcGTJAw88YN52223B/TuHoX772982d+3aZS5ZsuSkYagffPCBabfbzYcfftgsKCgwH374YcuHEZ/t9b344oumw+Ewn3jiiVMOy//Rj35kvvXWW+aBAwfMzZs3m1/60pdMh8NhfvTRR/1+fabZ82v81a9+Zb766qvm3r17zR07dpgPPPCACZjLly8P7jOQP8NOX/ziF82ZM2d2+56h9Bk2NjaamzdvNjdv3mwC5qOPPmpu3rw5OJpyoH8HTbPn1zjQvoc9vb5Q+Q4q3PTA0aNHzS984QtmTEyMGRMTY37hC184abgbYC5dutQ0TdNsaWkx586dayYlJZlOp9PMysoy77jjDrO4uLjLMa2treY999xjJiQkmJGRkeYNN9xw0j79oafXd+jQIRPo9vHee++ZpmmaxcXF5mWXXWYmJCSYLpfLHD16tHnfffedNNdPX3niiSfMESNGmC6Xy5w2bZq5atWq4Gt33HGHefnll3fZf+XKlebUqVNNl8tlZmdnm0899dRJ7/nnP//ZzM3NNZ1Opzlu3LguX9r+1pPru/zyy7v9rO64447gPt/61rfMrKws0+VymUlJSebcuXPNNWvW9OMVnawn1/jzn//cHD16tBkREWEOHTrUvOSSS8w33njjpPccqJ+haQamj4iMjDSfeeaZbt8vlD7DzmHBp/pvLhy+gz29xoH2Pezp9YXKd9AwzWO9tURERETCwKDvcyMiIiLhReFGREREworCjYiIiIQVhRsREREJKwo3IiIiElYUbkRERCSsKNyIiIhIWFG4ERERkbCicCMiIiJhReFGREREworCjYiIiIQVhRsREREJK/8/pUNLg+DIhAcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(mm_scaled,columns=['A','B','C'])\n",
    "df.plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5b05c063",
   "metadata": {},
   "outputs": [],
   "source": [
    "rscaler = RobustScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a4dc078d",
   "metadata": {},
   "outputs": [],
   "source": [
    "robust = rscaler.fit_transform(df)\n",
    "df = pd.DataFrame(robust, columns=['A','B','C'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "75b31a1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.kde()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "337645b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 1, 1],\n",
       "       [1, 0, 1],\n",
       "       [1, 0, 0]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "binary = Binarizer(threshold=5)\n",
    "\n",
    "a = np.array([[ 30, 10,  22],\n",
    "              [ 20,  2,  10],\n",
    "              [ 33,  5, 5]])\n",
    "\n",
    "binary1 = binary.transform(a)\n",
    "binary1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "632b3461",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = [[5, 2, 3],\n",
    "     [2, 4, 10],\n",
    "     [6, 8, 6]]\n",
    "\n",
    "sss = [np.sqrt(np.sum(np.power(X[i], 2))) for i in range(len(X))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "046f6713",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b59ef4fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.81110711, 0.32444284, 0.48666426],\n",
       "       [0.18257419, 0.36514837, 0.91287093],\n",
       "       [0.51449576, 0.68599434, 0.51449576]])"
      ]
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     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "np.array([X[k] / sss[k] for k in range(len(X))])"
   ]
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  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "91113de0",
   "metadata": {},
   "outputs": [],
   "source": [
    "normalizer = Normalizer()\n",
    "data_tf = normalizer.fit_transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c838b6b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.81110711, 0.32444284, 0.48666426],\n",
       "       [0.18257419, 0.36514837, 0.91287093],\n",
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     "execution_count": 22,
     "metadata": {},
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    "data_tf"
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  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "3dbcc99d",
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   "outputs": [
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       "  TEAM  YEAR\n",
       "0    A  2000\n",
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     "execution_count": 24,
     "metadata": {},
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    "dff = pd.read_csv(\"/Users/shridharmankar/encoding.csv\")\n",
    "dff"
   ]
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  {
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   "execution_count": 25,
   "id": "37371266",
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       "   TEAM  YEAR\n",
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       "2     2  2003\n",
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       "5     2  2006\n",
       "6     1  2007\n",
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       "8     3  2009"
      ]
     },
     "execution_count": 25,
     "metadata": {},
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    "le = LabelEncoder()\n",
    "df1 = dff\n",
    "df1.TEAM = le.fit_transform(df1.TEAM)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "90f16257",
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   "source": [
    "enc = OneHotEncoder()\n",
    "enc_df1 = pd.DataFrame(enc.fit_transform(df1[['TEAM']]).toarray())\n",
    "enc_df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "898ea916",
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "   TEAM  YEAR    0    1    2    3\n",
       "0     0  2000  1.0  0.0  0.0  0.0\n",
       "1     1  2002  0.0  1.0  0.0  0.0\n",
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       "3     3  2004  0.0  0.0  0.0  1.0\n",
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       "5     2  2006  0.0  0.0  1.0  0.0\n",
       "6     1  2007  0.0  1.0  0.0  0.0\n",
       "7     0  2008  1.0  0.0  0.0  0.0\n",
       "8     3  2009  0.0  0.0  0.0  1.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abc = df1.join(enc_df1)\n",
    "abc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d64a6de4",
   "metadata": {},
   "outputs": [
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       "   YEAR    0    1    2    3\n",
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       "6  2007  0.0  1.0  0.0  0.0\n",
       "7  2008  1.0  0.0  0.0  0.0\n",
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   ],
   "source": [
    "final = abc.drop(['TEAM'], axis='columns')\n",
    "final"
   ]
  }
 ],
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