Major Project .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Q. WHO has hired you for working on the dataset of COVID-19. Aggregate data and within 2 days present your point of view to the joint commitee on strategic plannig to fight against COVID-19\n",
    "\n",
    "## A. Present state analytics - India\n",
    "## Allotted state - Maharashtra\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 444,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt   #importing required libraries\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 445,
   "metadata": {},
   "outputs": [],
   "source": [
    "dateCols = ['Date']\n",
    "\n",
    "data = pd.read_csv(\"covid-19.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3711 entries, 0 to 3710\n",
      "Data columns (total 9 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   Sno                       3711 non-null   int64 \n",
      " 1   Date                      3711 non-null   object\n",
      " 2   Time                      3711 non-null   object\n",
      " 3   State/UnionTerritory      3711 non-null   object\n",
      " 4   ConfirmedIndianNational   3711 non-null   object\n",
      " 5   ConfirmedForeignNational  3711 non-null   object\n",
      " 6   Cured                     3711 non-null   int64 \n",
      " 7   Deaths                    3711 non-null   int64 \n",
      " 8   Confirmed                 3711 non-null   int64 \n",
      "dtypes: int64(4), object(5)\n",
      "memory usage: 261.1+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 447,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sno</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>State/UnionTerritory</th>\n",
       "      <th>ConfirmedIndianNational</th>\n",
       "      <th>ConfirmedForeignNational</th>\n",
       "      <th>Cured</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>30/01/20</td>\n",
       "      <td>6:00 PM</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>6:00 PM</td>\n",
       "      <td>Kerala</td>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>01/02/20</td>\n",
       "      <td>6:00 PM</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "   Sno      Date     Time State/UnionTerritory ConfirmedIndianNational  \\\n",
       "0    1  30/01/20  6:00 PM               Kerala                       1   \n",
       "1    2  31/01/20  6:00 PM               Kerala                       1   \n",
       "2    3  01/02/20  6:00 PM               Kerala                       2   \n",
       "\n",
       "  ConfirmedForeignNational  Cured  Deaths  Confirmed  \n",
       "0                        0      0       0          1  \n",
       "1                        0      0       0          1  \n",
       "2                        0      0       0          2  "
      ]
     },
     "execution_count": 447,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 448,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Sno',\n",
       " 'Date',\n",
       " 'Time',\n",
       " 'State/UnionTerritory',\n",
       " 'ConfirmedIndianNational',\n",
       " 'ConfirmedForeignNational',\n",
       " 'Cured',\n",
       " 'Deaths',\n",
       " 'Confirmed']"
      ]
     },
     "execution_count": 448,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_col = []\n",
    "\n",
    "for col in data.columns:   #printing columns to eliminate column which is not necessay \n",
    "    data_col.append(col)\n",
    "    \n",
    "data_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 449,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Sno</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>State/UnionTerritory</th>\n",
       "      <th>ConfirmedIndianNational</th>\n",
       "      <th>ConfirmedForeignNational</th>\n",
       "      <th>Cured</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Confirmed</th>\n",
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       "      <th>417</th>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>1969</th>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "        Sno   Date   Time  State/UnionTerritory  ConfirmedIndianNational  \\\n",
       "417   False  False  False                 False                    False   \n",
       "1868  False  False  False                 False                    False   \n",
       "3066  False  False  False                 False                    False   \n",
       "1969  False  False  False                 False                    False   \n",
       "2883  False  False  False                 False                    False   \n",
       "\n",
       "      ConfirmedForeignNational  Cured  Deaths  Confirmed  \n",
       "417                      False  False   False      False  \n",
       "1868                     False  False   False      False  \n",
       "3066                     False  False   False      False  \n",
       "1969                     False  False   False      False  \n",
       "2883                     False  False   False      False  "
      ]
     },
     "execution_count": 449,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sample(5).isna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 450,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>State/UnionTerritory</th>\n",
       "      <th>Cured</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30/01/20</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>31/01/20</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>0</td>\n",
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       "      <th>2</th>\n",
       "      <td>01/02/20</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>0</td>\n",
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       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>02/02/20</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>03/02/20</td>\n",
       "      <td>Kerala</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3706</th>\n",
       "      <td>03/07/20</td>\n",
       "      <td>Tripura</td>\n",
       "      <td>1146</td>\n",
       "      <td>1</td>\n",
       "      <td>1435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3707</th>\n",
       "      <td>03/07/20</td>\n",
       "      <td>Uttarakhand</td>\n",
       "      <td>2405</td>\n",
       "      <td>42</td>\n",
       "      <td>2984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3708</th>\n",
       "      <td>03/07/20</td>\n",
       "      <td>Uttar Pradesh</td>\n",
       "      <td>17221</td>\n",
       "      <td>735</td>\n",
       "      <td>24825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3709</th>\n",
       "      <td>03/07/20</td>\n",
       "      <td>West Bengal</td>\n",
       "      <td>13037</td>\n",
       "      <td>699</td>\n",
       "      <td>19819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3710</th>\n",
       "      <td>03/07/20</td>\n",
       "      <td>Cases being reassigned to states</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6031</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3711 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Date              State/UnionTerritory  Cured  Deaths  Confirmed\n",
       "0     30/01/20                            Kerala      0       0          1\n",
       "1     31/01/20                            Kerala      0       0          1\n",
       "2     01/02/20                            Kerala      0       0          2\n",
       "3     02/02/20                            Kerala      0       0          3\n",
       "4     03/02/20                            Kerala      0       0          3\n",
       "...        ...                               ...    ...     ...        ...\n",
       "3706  03/07/20                           Tripura   1146       1       1435\n",
       "3707  03/07/20                       Uttarakhand   2405      42       2984\n",
       "3708  03/07/20                     Uttar Pradesh  17221     735      24825\n",
       "3709  03/07/20                       West Bengal  13037     699      19819\n",
       "3710  03/07/20  Cases being reassigned to states      0       0       6031\n",
       "\n",
       "[3711 rows x 5 columns]"
      ]
     },
     "execution_count": 450,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.drop(columns=['Sno','Time','ConfirmedIndianNational','ConfirmedForeignNational'],inplace=True)\n",
    "data #dropping unecessay columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 451,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.set(style='ticks')\n",
    "#b = sns.pairplot(data)\n",
    "#b.map(plt.plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = data[\"State/UnionTerritory\"] == 'Maharashtra'\n",
    "Maharashtra = data.loc[temp]\n",
    "\n",
    "temp = data[\"State/UnionTerritory\"] == 'Tamil Nadu'\n",
    "TamilNadu = data.loc[temp]\n",
    "\n",
    "temp = data[\"State/UnionTerritory\"] == 'Delhi'\n",
    "Delhi = data.loc[temp]\n",
    "\n",
    "temp = data[\"State/UnionTerritory\"] == 'Gujarat'\n",
    "Gujarat = data.loc[temp]\n",
    "\n",
    "temp = data[\"State/UnionTerritory\"] == 'Uttar Pradesh'\n",
    "UttarPradesh = data.loc[temp]\n",
    "\n",
    "temp = data[\"State/UnionTerritory\"] == 'Rajasthan'\n",
    "Rajasthan = data.loc[temp]\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Insight of top 5 States"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Maharashtra analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 453,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "76      09/03/20\n",
       "757     08/04/20\n",
       "1723    08/05/20\n",
       "2757    07/06/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 453,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Maharashtra.Date[0:118:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7ZOrJyMiowQTDzs6OJBIJN23x4sW0dOlSImr8WvL29qaJEydy8xqKXyqVkqWlJe3YsUNmfS4uLuTl5cWtr6Fr/dixY3Tr1i2Z+WZmZnTs2DEiajjB8PDwoI8++khm2tatW2nEiBFERNx18bxzrvb54+fnRytXriQiIolEQjY2NnT37l2ZBOP27dt09OhRmXV89dVXNH/+fCL637Vee38CAwPJwcGBiIgyMzNpz549MuV37txJ48aNkykfFxfHzW/sO2vRokW0cOFC7jrJzs6m69ev19k/IuISjJycHG5d4eHhFBUVJbP+KVOm0C+//FJvndX233//0fjx4+n999/nEnVDQ0Muqa/xzTff0IIFC1q8fEOUm9LK4e7ujmnTpkEsFuO3337D2bNn8cknn2DAgAEAgLKyMjx69Ah+fn744osvuHJisZi7lVKbhYUFbt68iY0bN+LevXtISUnBvXv3MH369EZjSUlJgZGREVRVVblpJiYmEAgESEtLg6GhIQDINKl17Nix0c6Fte/xGRgYQCAQIDU1FdnZ2RCJRPU+xXLv3j3o6+vLTBMKhVBWVkZ8fDxycnJgamoKKysrxMTEYOHChYiKisJPP/3UaJ01tU579eols311dfUX6kj5IuVTUlIQHx8vcwuoqqoKffr0AQCkpaXBycmJm8fj8fDZZ58BALKzs+usKzk5GSdOnOCmVVdXQ1lZmZs/bdo0mXWZmJg0eb+e58CBA1BTU8Pjx4+xbt06dOvWDZ6enujQoQMAIDU1tcHj/eDBA7z11lvQ1tbmpo8cORIAcPLkSQgEAgwaNIib98Ybb2DgwIFcD+wpU6YgLCwMixYtwvnz56Gurg4rK6smH++ePXty/1/Tsdje3l4mTpFIhHv37qGiogIqKircdQoApqamz60bqVQKd3d3vPnmm9i8eTN+//13fPPNNxgyZAg2bNiAkSNHYuXKlQ3Ubl01ty47derUpHgFAgEMDAy4eSYmJjAxMUFycjLEYjFcXFxkOvxVVlbi3r17AIAPPvgAp06dQkhICDIyMnDnzh0AT29vaGpqwt3dHX5+fggICMDo0aMxefJkmJqaNlr3hYWFyMvLw8CBA7l53bt3b7RfklAolLn1Zmpqyt3jbuxaAmSPdUPx5+XlobCwsE4/hSFDhsjcM2/oWp82bRrOnz+P48ePIyMjA4mJiSgvL4dUKm1wH2v2pfa1WrPtH3/8ket/0VTjx4/HZ599BolEgri4OKirq9f5jB04cCBUVVXxyy+/ID09HWlpaUhJScGQIUNklqtdfxoaGlzzf8+ePWFnZ4dt27YhNTUV6enpSEpKqnM8a5dv7DvL3d0d7u7usLa2xrBhwzB+/Hi88847z91PNTU1dO3alfv3uHHjcPXqVXz33XfIyMjA3bt3kZWVBTs7uwbr68GDB3BxcYGysjKCgoK4z09VVdU6t5TFYrHM92ZLlG9MkxIMLS0t7uT84osvUFBQgMWLFyMsLAxvvvkmdxKuX79e5iKsCfRZR48exZo1azBz5kyMHDkSS5YswebNm5sUcEM7WPtiEAgEMvOokY42tfuS1F5HdXU19PT0EBISUmd+fR1PlZWVMXz4cFy9ehW5ubmwsLDAsGHDsGvXLty+fRuVlZUYOnQod7I/r86aWqf1JXCN7WttL1JeIpFg+fLlGDNmjMz0mpNSIBA0ube3RCKBo6Mj5syZ89xlno1DIBA8955kU7399ttQV1dHr169sH37dkybNg2+vr7c+dfY8X62n0htNUnKs+hpSyGApwnGDz/8gHv37uHkyZNwcHAAn89v8vGu/f8SiQQCgQDHjh2rU++dO3fGlStXuO3XzH/2uqgtOTkZSUlJ+Omnn6CiogJHR0fEx8dj2bJlePLkCVatWvXcss+TmJgI4GnSfufOnQbjjYmJee75U3Pcd+3aVee669ixI4gILi4uyMnJweTJk2FtbY3+/fvLJDNeXl6YMWMGIiIicPHiRTg7O2Pp0qWYO3cugMbrvr7zsSHPfqZIpVIu4WjsWnp22w3FP2/evHq3T0Qyn4kNXeuff/45oqKiMH36dEyfPh1r1qxp8Auytvo+k2vW25QEpTZra2tIJBLExMTg/PnzmDhxYp1loqKi8NFHH2Hy5MkYNmwYnJycEBYWhrt378osVzu5qy05ORnvv/8+bGxsMGzYMMyaNQvx8fH47bffZJarfT039p1lZmaGiIgInD9/HpGRkdi4cSN+++03HD58uN4Ynv2sCAgIwJ49e/Duu+/Czs4OK1asgJeXV4N1lZqaCicnJ+jo6GDXrl0yP3q6detWp09Kbm4uunXr1mLlm6JZnTy/+OIL8Pl8rFmzBsDTXyddu3bFf//9h169enF/+/btw6VLl+qU379/P1xcXLBmzRrMmjULBgYGyMzM5E7Khr6k+vXrh6SkJJnHZW7duoWqqir07du3ObsDADInZ+319evXDzk5OdyXUq9evSAQCLB+/XoUFBTUu66RI0fiypUriIuLw7Bhw2BiYoLKykqEhITAxsYGAoGg0Tp70TptDf369UNWVpZMPH///TfXCtG7d2/cvn1bpszkyZNx+vTpOse0X79+yMzMlFnXtWvXuIvcwMAA8fHxMmVqfpG2lO7du8PHxwenT5/mfuk1drx79+6NR48eyXQC/uOPP/Dee++hX79+qKqqwq1bt7h5IpEISUlJ3C/Tbt26YejQoThx4gQuXbqEqVOnAnjxawgA+vbti6qqKohEIm75rl27cr+CDAwMIBaLuS95AHWOT21qamoAIDMWgb+/P6qrq6GhoYHBgwe/aBUjNDQUZmZm0NPTazTePn36QCwWyzzyfe3aNYwePRpvv/02lJWVUVBQwJXt2bMnAgICkJCQgNTUVERHR2P79u3w8PDAhAkTuM6hRIRHjx7hiy++wFtvvQVXV1fs3bsXbm5uCAsLa7TutbS00LVrV5lxfwoKChod1+DZ8zUhIYFrYW3sWnpWQ/F37NgRurq6dTqIx8XFNekzsbS0FMePH8eGDRvg5eWFSZMmQSAQoKSkpEk/Vvr27VvvtnV0dJ77SOrzCAQC2NraIjw8HGfOnKn3F/zBgwcxadIkbNiwAR988AFMTU1lvj8ac+zYMQwcOBC//PILFixYgGHDhuHhw4cNlm/sO2vr1q1ISEjA1KlT8f333+P3339HcnIy7t6926QfXfv374e3tzd8fHwwffp09OjRA48ePXpuTNnZ2XBycsKbb76JPXv21Em6hUKhzBg0VVVViIuLg1AobJHyTdWsBENbWxvLly/HhQsXEB4eDgBwdXVFUFAQTp48iQcPHiAoKAj79++XafKroampiejoaKSmpiIlJQWrV69Gamoq1yTzxhtvAHj6YfjsOBtTp05Fhw4dsHLlSiQnJyMmJgarVq3C8OHD0b9//+bsDgDgm2++wbVr15CQkAA/Pz9MmjQJb7/9NmxsbDBgwAAsW7YMt27dQlJSEj777DOuqRx42tSYlpbGfTCPGjUKCQkJyMzMhJmZGdcD98SJExg1ahS3zcbq7EXqtDW4urri4MGDOHDgAO7fv4/Q0FAEBARw9eDk5ISDBw8iLCwM9+/fx48//oi8vDwMGzaszjF1dnbGhQsXsGXLFmRmZuL06dP45ptvuBN9/vz5iIyMREhICO7du4eNGzc2OOCTRCJBbm7uCz+nPXPmTAwbNgzffvstysvLGz3eI0aM4MaGqDn/apqse/fuDTs7O3z++eeIiYlBcnIyvL29wefzZZ7EmDZtGnbu3Ilu3brJ3LJ40ePdt29fjB07FitXrkRMTAzS0tLg7e2N+Ph49O3bF3379sXo0aOxatUqJCQkICYmBt9///1z66JXr16wsrLCl19+ibi4OCQlJcHLywtaWlpQVlbG0qVLIRKJnlu+qKgIubm5+O+//3Dnzh34+/sjPDwcvr6+TYq3X79+GDFiBFavXo1bt27h9u3bWL9+PaytrdGxY0d88MEHWLduHS5evIjMzEx89dVXiIiIQL9+/aChoQE+n48TJ04gKysL//zzD7y9vQE8bdrV1tbG6dOnsW7dOmRmZuL27dv4559/uNtuDdU9j8eDk5MTgoODER4ejpSUFPj6+jbamnbnzh2uST0kJASXLl2Co6Mjt72GrqVnNRb/Rx99hC1btuDEiRPIyMhAUFAQLl++zG2vIR06dICamhrOnj2LBw8e4Pr16/Dw8AARNenJLVdXV1y6dAlBQUHIyMjAyZMnsW3bNjg6OjZr/IoJEyZwLYW1bzfW0NTUREJCAm7fvs19NkRGRjb5KTMtLS2kp6cjJiYGDx48wK+//opDhw41WL6x76zs7Gx8/fXXiI2NxYMHD3Ds2DF07NgRvXv35j77EhMTnzsWhqamJnde3759G56eniguLn5uTF9//TWqq6vx7bffQiwWIzc3F7m5udwtqXnz5iEiIgK//vorUlNTsWrVKqioqMDBwaFFyjdZY5006nuKhOhpp7s5c+bQmDFjqLy8nCQSCQUHB5OtrS0NGjSIpkyZQmfPnuWWr91JKC0tjT788EMyNTUlGxsbWrFiBf34449kZ2dHRE87frm7u5OxsTHt2rVLppMnEVFKSgotXLiQTExMyNLSkvz9/bmnWerrcPZs+dpqlq/pRW5mZkbLly+X6e38+PFj+uSTT0goFNKQIUNoyZIllJWVxc0PDQ0loVBI77zzDjdt6tSpXC9iIuJ6bdfu4NZYnTU2v3bHp8aOF1H9nTwbKv9sJ08iot9//53rAGhnZyfT6YyIKCQkhMaMGUOmpqb0/vvvc087PHtMiYjOnj1LU6dOJWNjY7K1taWgoCCSSqXcus6ePUv29vZkYmJCH3/8MS1fvvy5nTxrjuPzOt097ykSIqLk5GQyNjamDRs2EFHjxzszM5NcXV258/f777/nOkc9efKEfH19aejQoWRmZkZubm6Unp4us73i4mIaNGgQ/fzzzzLTX+Qaqr0uHx8fsrCwIDMzM1qwYIHMuV9SUkLLly8nMzMzGjVqFO3bt6/BDnf5+fm0bNkyEgqFZG5uTp9++illZ2fTzZs3aerUqVynyPrqvubP0NCQbGxsaMmSJdzxb2q8+fn59Omnn5JQKCQLCwtavXo1d8wqKyvp22+/peHDh5OpqSnNnj2b/v33X67soUOHaMyYMWRiYkL29va0Z88emjp1KteZ8saNGzRnzhwyMzOjYcOGkY+PD3edN1b3UqmUAgMDafjw4WRubk4bN26kiRMnNtjJ09nZmZYuXUomJiY0efJkOnfunMwyDV1L9V2bDcUvlUq5JxEGDRpEM2fOpAsXLjS4vtrX+rlz52jixIlkYmJC48aNo82bN5ObmxvXEbuhTp5ETzsp1lzL48aNo127dnHX8ot08iR62vnZ1NSU6wz/bPy5ubnk5uZGZmZmZGlpSYsWLaKdO3eSUCikioqKeq/12p9l5eXl5OXlRUOGDKGhQ4fS/PnzKTQ0lAwMDOjx48f1lm/sO6usrIxWrVpF1tbWNGjQIJo1a5ZMh+TPP/+cBg0aRF9//XW930dxcXE0ffp0MjExodGjR9PatWvp888/l3masUZlZSUZGhrKXHM1f7WP8cmTJ2n8+PFkampKc+fOpdTU1BYp/yJ4RAoyAhLDvKQdO3ZAT08PkyZNknco7RLV6svBNMzHxwfl5eVN7lvGMO0Re9kZ0y6Ulpbi5MmTsLa2lnco7RZLLhiGeRFNeoqEYRRdx44dcfDgwXp7yjMMwzCtj90iYRiGYRimxbFbJAzDMAzDtDiWYDAMwzAM0+JYgsEwDMMwTItjnTwV1KNHj5pVTk9Pr9llW4Mix8diaz5Fjo/F1nyKHt+z9PT05B0CUwtrwWAYhmEYpsWxBINhGIZhmBbHEgyGYRiGYVoc64PRxlRUVEAikTx3VMWsrKwGX0glb4ocX1ZWFiorK+t9/TTDMAzzYliC0YZUVVUBePr21ucRCAQKPaSzIscnEAhQWVmJqqoqCAQCeYfDMAzTprFbJG2IWCxGhw4d5B1Gu9ahQ4cmv/aZYRiGeT6WYLQxivrrv71g9cswDNMyWILRhrAvv9bB6plhWh+VFEOy9lNQZpq8Q2FaCOuDwTRbWVkZtm/fjjPQIJEAACAASURBVPj4ePD5fHTq1AmLFy+Gvr7+C6/rr7/+wu7duzFu3DhkZGRgxYoV6NKlyyuI+qn169fDzMwM9vb2r2wbDMM0HUVFAPfTAfZG5HaDJRhMs0ilUvj4+EAoFGLHjh3g8/mIi4uDj48PQkJC0Llz5xda37lz57By5UoMGzbsFUXMMIyiIiLQpbNAfyPw3nxb3uEwLYQlGEyzxMXFIScnB05OTlBSenqnTSgUYuXKlZBKpdi3bx/Cw8OhpKSEoUOHwt3dHbm5ufD390fv3r2RkpICLS0trFmzBseOHUNiYiI2bdoEDw8PbNq0CZs2bcKNGzdw+vRpFBcXw9raGvn5+VBVVUVKSgpKS0vh6uqKs2fPIi0tDTY2NliyZAkkEgm2bNmC+Ph4SCQS2NvbY9asWSAiBAUF4erVq9DR0YFUKoWZmZmca5FhGABAyh3gvyzwHN6TdyRMC2IJRhsljToH+ie87nQeD0T0Uuvm2YyH0vCxDS6TmpqK/v37c8lFDSsrK0RHRyMqKgpbtmyBQCCAv78/wsLCYG1tjdTUVHz22WcYMGAA/P39ER4ejgULFiAuLg5OTk51vvRzc3Oxe/du8Pl8rF+/Hvn5+QgMDMSpU6ewYcMG7N27Fx06dMCsWbMwf/58nDt3DgCwbds2iMVirFy5EgYGBigsLERqaipCQkJQWloKFxeXl6ojhmFaDl0+A6i9Ad5QG3mHwrQglmAwzcLj8Z47VkRsbCzGjh3LDVjl4OCAM2fOwNraGlpaWhgwYAAAoE+fPigpKWlwOwMGDACfz+f+bWFhAQDo3r07+vTpAy0tLQBAp06dUFpaiuvXryM1NRVxcXEAAJFIhPT0dGRmZmLkyJFQVlaGpqYmLC0tX64CGIZpEVReCrr+D3jWY8HrwAa5a09YgtFGKQ0fC9TTyiAQCLgBuV4lAwMDHD9+HEQk89TF9u3bERsbi4kTJ8osL5FIAAAqtTpw8ZrQ2vLsuB+1k5raiUcNqVQKd3d3jBo1CgBQXFwMNTU1bNmyRWZb9ZVlGKb1UXQkIBaDN9JO3qEwLYw9pso0i6mpKbS0tLB7924uebh27RpOnTqFd999F+fOnUNlZSUkEgn+/vvvVuvvIBQKceLECVRXV0MkEsHDwwN37tyBubk5Lly4ALFYjJKSEvz777+tEg/DMM9HRKCLfwNv9wGvV395h8O0MNaCwTQLj8fDunXrEBgYCGdnZygrK6Nz585Yv349BgwYgNzcXLi7u0MqlWLo0KGYOXMmcnNzX3lc06ZNw8OHD+Hm5gaJRAIHBwcuubl79y6cnZ2hra2NXr16vfJYGIZpROINICsTPKel8o6EeQV49LI9AtuA8vJy+Pn5wdvbGw8fPsSBAwe4eQUFBRgwYAB8fHxw6NAhnD9/nnvXx7hx42Bvb4+MjAxs2bIFIpEIRkZGcHNzA5/PR15eHgICAlBcXAw9PT14enpCVVUVZWVl2Lx5M3JycqChoYFly5ZBU1PzhWJ+9OhRvfvxxhtvNFiutW6RNJcix1cTW1PqubXp6enVe04oCkWOj8XWfK86PsmmL4CHGVD6dgd4LfD+Hz09vRaIimkp7b4FIyUlBVu3buUuEnNzc5ibmwMAioqK4OfnhwULFgAA0tLS8Omnn9YZKCogIADu7u7Q19dHcHAwIiIiYGdnhx07dsDOzg42NjY4fPgwDh8+jHnz5uHgwYMwMjKCr68vIiMjERISgmXLlrXujjMMwygwysoEbseBN31eiyQXjOJp930wIiIi4OLiAm1t7Trz9u7diwkTJuDNN98EAKSnp+Po0aNYsWIFdu7cCbFYjNzcXIjFYi7psLW1xZUrV1BdXY3ExERYWVlx069evQrg6VMUI0aMAADY2Njgxo0bqK6ubo3dZRiGaRPo7HFARQW80Ww03faq3bdgLFq0qN7pjx8/xp07d7j5FRUV6NOnDxwdHdG9e3cEBgbiyJEjGDJkiMztDS0tLRQUFKCkpARqamrc0whaWlrIz88HABQWFnKPT/L5fKipqeHJkyd1kpyysjKUlZXViU1XV/fld5xhGEZB0ZNCUPQF8EZMAK+jhrzDYV6Rdp9gPE94eDjs7Oy4xx5VVVXh6+vLzZ86dSqCg4MhFAplHsOseSzz2cczAXCDTj3brYWI6gxIBQAnTpzA4cOH60wPDQ2t915iVlbWc8eeqK0py8iTIscnEAigpqamkPdyFTGm2hQ5PhZb872K+IpOHUaJRIJuH7pCoOD7zzTfa5tg/Pvvv1i9ejX377y8PCQkJGDs2KdjSxAR+Hw+dHR0UFhYyC1XVFQELS0taGhooLy8HFKpFEpKSjKtFtra2igqKoKOjg4kEgkqKirQsWPHOjFMnjwZtra29cZXX8cqkUjU6Js+FbkTJaDY8dXEJhKJFK7j3eveGfBlsNia71XER08KIf3zd/AsRiGXJwBacP2Knqy9btp9H4z6PHnyBGKxWOZWhIqKCvbv34+cnBwQEU6fPg0LCwt07doVKioqSEpKAgBERkZCKBRCWVkZhoaGiIqK4qbXPA4pFApx8eJFAEBUVBQMDQ2hrFw3l1NXV4eurm6dP4ZhmPaKTh0FqqrAmzJH3qEwr9hr2YKRk5MDHR0dmWkaGhpwc3PDhg0bUF1dDQMDA0ydOhUA4OHhga1bt0IkEqFPnz5wcHAAALi6unJ9Nbp06YKlS58+yz1nzhwEBgbCy8sL6urq8PDwaN0dZBiGUUBUVAC68Dd4VrbgdX9L3uEwr9hrMQ5GW9QWxsHIzs6Go6MjN2iVWCyGsbEx3Nzc6n1qp7H4NmzYgAULFqB79+6YM2cONm3ahO7du7+y+J8XGxsH48UpcnwstuZr6fikB7eDzp+A0tpg8HTfbLH11mC3SBTLa3mLhGk5Ojo62LFjB3bs2IHdu3dDW1sba9asada6al5QxjBM+0NFBaCLp56+1OwVJBeM4nktb5G0B+fSixGRVlRnOo+nBCLpS617XD9NjO3b+YXL8Xg8ODk5YebMmUhLS0N0dDQuXLgAiUSCYcOGwd3dHQCwY8cOxMbGoqSkBDo6OvD398epU6eQn58PHx8f/PzzzwCA3bt3IzU1FZWVlfDx8cHAgQMRGhqK06dPQ0lJCYaGhli+fPlL7SvDMK2DwsMAiQS8Se/JOxSmlbAWDKZFCQQC9OjRA6mpqUhOTkZwcDC2b9+OvLw8hIeH4+HDh7h//z5++eUX7N27F7q6uggPD8eHH34IHR0drF+/Hp07P01uevfuje3bt2PGjBkIDQ2FRCLBb7/9hq1bt2Lr1q2orq5ulfebMAzzcqi8FHTxb/CG2oCny25jvC5YC0YbNbZv53pbGRTlMdAjR46guLiYa7UQi8Xo1q0bJk2ahCVLluDEiRN48OAB7ty5g7feqr+zV81oqL1790ZkZCT4fD6MjY2xaNEi2NjYYPbs2ejatWur7RPDMM1D508CFSLw7N+VdyhMK2IJBtOiqqqq8ODBAwiFQowfPx6zZ88GAJSWloLP5yMpKQlr1qzBrFmzMHr0aCgpKdUZmKxGzSipNQObAcDXX3+NO3fuIDo6GitXrsSqVata7VXwDMO8OBJXgiL+BAYNAa9nX3mHw7QidouEaTFSqRS//vorBg4cCAcHB5w9exYikQgSiQSrV6/GxYsXcePGDQwePBjTpk1Djx49cPXqVUilT/uM8Pl8SCSS566/qKgITk5O6Nu3L5ydnTF06FCkp6e31u4xDNMM9E84UFIMJQfWevG6YS0YzEvJz8+Hq6srgKcJRv/+/eHn54dOnTohLS0NixcvhlQqhYWFBSZOnIji4mL4+vrC2dkZAKCvr4/Hjx8DAKytreHj44Pvvvuu3m1pampiypQpWLRoETp06IC3336bG5OEYRjFQ1LJ05ea9TMEBhjLOxymlbFxMBRUWxgHozkUOT42DkbzKXJ8LLbme9n46HoUpFvWQ2mxD3jmw1swsvqxcTAUC7tFwjAMw7wS0jPHgK7dATNLeYfCyAFLMBiGYZgWR6mJQPpd8Ca8A54SX97hMHLAEgyGYRimxUnPHAPe6Aje8HHyDoWRE5ZgMAzDMC2Kch4DN6LBs50EXgdVeYfDyAlLMBiGYZgWRZfPADweeGPYU16vM5ZgMAzDMC2GJBJQ1DnAZCh4mjryDoeRIzYOBtNsZWVl2L59O+Lj48Hn89GpUycsXrwY+vr6Lbqd9evXw8zMDPb29i26XoZhXoGbMUBxIZRGTJB3JIycsQSDaRapVAofHx8IhULs2LEDfD4fcXFx8PHxQUhICPfCMoZhXi/Sy2eBzlqAyVB5h8LIGUswmGaJi4tDTk4OnJycoKT09E6bUCjEypUrERsbi+PHj2PTpk0A/tcCYWZmBm9vb2hoaKBDhw7YsGEDtmzZgvj4eEgkEtjb22PWrFkgIgQFBeHq1avQ0dGBVCpl7xthmDaAigqAmzHgTZwBHp89mvq6YwlGG/XgnhgP7lXWmc7jKYFI+lLrfrtPB7zdR6XBZVJTU9G/f38uuahhZWWFGzduPLfc/fv3ceDAAXTv3h1hYWEAgG3btkEsFmPlypUwMDBAYWEhUlNTERISgtLSUri4uLzU/jAM0zroyjlAKgXPht0eYV6TBKO8vBx+fn7w9vaGrq4ugoKCkJSUhA4dOgAAZs2aBQsLCyQkJGDPnj0Qi8UYPnw45syZAwDIyMjAli1bIBKJYGRkBDc3N/D5fOTl5SEgIADFxcXQ09ODp6cnVFVVUVZWhs2bNyMnJwcaGhpYtmwZNDU15VkFLY7H40EgELxwOS0tLXTv3h0AcP36daSmpiIuLg4AIBKJkJ6ejszMTIwcORLKysrQ1NSEpSUbBZBhFB1JJKDI04D+IPC6sSG7mdcgwUhJScHWrVtlxtNPS0vDl19+CS0tLW6aWCxGcHAwvvzyS+jo6GD9+vWIi4uDUChEQEAA3N3doa+vj+DgYERERMDOzg47duyAnZ0dbGxscPjwYRw+fBjz5s3DwYMHYWRkBF9fX0RGRiIkJATLli1r0f16u49Kva0MrfWuDwMDAxw/fhxEBB6Px03fvn07VFRUZF7BXl1dzf1/TVIHPO3H4e7ujlGjRgEAiouLoaamhi1btsiU57OmVoZReBR9Ecj7D0rvu8o7FEZBtPvHVCMiIuDi4gJtbW0AQGVlJfLy8hAcHIwVK1YgNDQUUqkUqampePPNN6Grqws+n4+RI0fiypUryM3NhVgs5p6MsLW1xZUrV1BdXY3ExERYWVlx069evQoAiI2NxYgRIwAANjY2uHHjhsyXbHtgamoKLS0t7N69m3vF+rVr13Dq1CkMHjwYjx8/hlgsxpMnT3Dz5s161yEUCnHixAlUV1dDJBLBw8MDd+7cgbm5OS5cuACxWIySkhL8+++/rblrDMO8IJJIQCdCgbf7AIMt5B0OoyDafQvGokWLZP5dVFSEQYMGwdXVFW+88QbWr1+Pc+fOQVVVVeY2hqamJgoKClBYWCgzXUtLCwUFBSgpKYGamhr361pLSwv5+fkAgMLCQq51hM/nQ01NDU+ePOGSnBplZWUoKyurE7Ourm7L7PwrxOPxsG7dOgQGBsLZ2RnKysro3Lkz1q9fjwEDBsDKygoLFy5Et27dYGJiUu86pk2bhocPH8LNzQ0SiQQODg5cZ867d+/C2dkZ2tra6NWrV2vuGsMwL4j+vQTkPILSYl+ZFk3m9dbuE4xndevWDZ999hn3bwcHB1y8eBFWVlZ1LgwejwepVCozveaWwLO3BgBwHR5rN+/X/PvZzpAAcOLECRw+fLjO9NDQ0HpfO5yVldWkfg/N6RvRHF26dMEXX3xR7zxvb+96p9feX4FAgOXLl9e73KJFi+okh61BIBBATU1NIV/7rIgx1abI8bHYmq+x+EgiQfbpI+D17o9uk2aAV89nHfN6eu0SjPv37+PRo0fcrQ0iAp/Ph46ODoqKirjlioqKoKWlBR0dHRQWFtaZrqGhgfLyckilUigpKcm0Wmhra6OoqAg6OjqQSCSoqKhAx44d68QyefJk2Nra1htn7T4jNUQiUaO/DlqrD0ZzKXJ8NbGJRKJ661+e9PT0FC6m2hQ5PhZb8zUlPum1SNDDTCi5r8Tj7OxWiqx+ip6svW5eu1STiLB7926Ulpaiuroa4eHhsLCwQP/+/fHo0SNkZ2dDKpXi8uXLEAqF6Nq1K1RUVJCUlAQAiIyMhFAohLKyMgwNDREVFcVNr2neFwqFuHjxIgAgKioKhoaGUFaum8upq6tDV1e3zh/DMExbQBIJ6M8DgF5PwHy4vMNhFMxr14LRq1cvTJ8+HX5+fpBIJLC0tOQ6ZC5ZsgQ//vgjxGIxhEIh18rh4eGBrVu3QiQSoU+fPnBwePoCH1dXVwQGBuLIkSPo0qULli5dCgCYM2cOAgMD4eXlBXV1dXh4eMhnZxmGYV4huhYJZGdBaZEPuzXC1MGjZzsMMAqhvmbJsrIyqKurN1hOkW9BAIodX01sTann1tYemtLlhcXWfA3FR9XVkPovAVTVoLR6o0IkGOwWiWKR/xnBNJmSklK7e9xV0VRXV9fbIZdhGFl05RyQmw2ld+YqRHLBKJ7X7hZJW6aqqoqKigpUVlY+t7OnmpoaRCJRK0fWdIocn5qaGqqqqqCqqirvUBhGoVGV+Om4F330AdNh8g6HUVAswWhDeDwe1NTUGlymLTe5ypsix8YwioROHgLyc6C0wIONe8E8F2vXYhiGYZqMsu6D/j4CnpUteEaD5R0Oo8BYgsEwDMM0CUmlkO79BVBTA282e8sx0zCWYDAMwzBNQhf/BtKSwJvtCl6nzvIOh1FwLMFgGIZhGkX300GHQgBjIXhWtvIOh2kD2kyCUVlZieTkZADAmTNnEBwcjLy8PDlHxTAM0/5ReSmkW9YD6p2g5LyMdexkmqTNJBhBQUGIiYlBamoqwsLCoKOjg61bt8o7LIZhmHaNiCAN+RkoyIWS+0rwNDQbL8QwaEMJRk5ODj788ENcv34dtra2mD17NkpLS+UdFsMwTLtG504AN6LBe28heP2N5B0O04a0mQSjZgTL+Ph4DBo0CFKpFBUVFXKOimEYpv2qfvwQdHQ3YDIUvHFT5R0O08a0mYG2DAwMsGzZMvD5fOjr62Pt2rUwMTGRd1gMwzDtEkmlKAj4CuArQ8nxY9bvgnlhbSbBcHZ2RnJyMnr27AklJSVMnTqVez06wzAM07Lo/ElU3ooFz8kTPC0deYfDtEFt5haJkpISioqKEBYWhsrKSpSXl7OXUjEMw7wClJsNOrobqkOHgzd8nLzDYdqoNvMN/ccff+DMmTO4cuUKxGIxDh8+jMOHD8s7LIZhmHaFiCDdFwzwlKD1yefs1gjTbG0mwfjnn3/g6+uLDh06oFOnTli3bh3++ecfeYfFMAzTrtDVC8CdOPDenQ/lrt3lHQ7ThrWZBENZWRkCgYD7t7q6Ovh8vhwjYhiGaV+opBgUugPoZwjeaAd5h8O0cW2mk6eOjg5iY2PB4/FQVVWFP//8E126dGlS2fLycvj5+cHb2xu6uroIDw/H33//DQDo168fPvroIygrK+PQoUM4f/481NXVAQDjxo2Dvb09MjIysGXLFohEIhgZGcHNzQ18Ph95eXkICAhAcXEx9PT04OnpCVVVVZSVlWHz5s3IycmBhoYGli1bBk1NNjgNwzCKjX7fAYhEUJr/CXisjxvzktrMGeTs7Iy//voLmZmZcHR0RFxcHFxcGn+bX0pKCvz9/fHo0SMAwKNHjxAWFoa1a9fihx9+gFQqxalTpwAAaWlp+PTTT/H999/j+++/h729PQAgICAAzs7O+Pnnn0FEiIiIAADs2LEDdnZ22LRpE/r27cv1CTl48CCMjIywceNGjBs3DiEhIa+iShiGYVoM3bwOir4I3qT3wNPrKe9wmHagzSQY2tra8Pf3x+7duxESEoK1a9eia9eujZaLiIiAi4sLtLW1AQACgQCurq544403wOPx0LNnT+6dJunp6Th69ChWrFiBnTt3QiwWIzc3F2KxGPr6+gAAW1tbXLlyBdXV1UhMTISVlRU3/erVqwCA2NhYjBgxAgBgY2ODGzducAOFMQzDKBqqEEG6Lwh4823wHGbJOxymnWgzCUZWVhYiIiKgoqKCrVu3wsPDA7du3Wq03KJFi2Bk9L/hbbt27QpTU1MAwJMnT3D69GkMGzYMFRUV6NOnDxwdHbFhwwaUlZXhyJEjKCwslLm9oaWlhYKCApSUlEBNTY3rB6KlpYX8/HwAQGFhIbS0tAAAfD4fampqePLkSZ3YysrKkJOTU+ePYRimNdEf+4DCvKe3Rmr1dWOYl9Fm+mBs27YN48ePR2xsLPLz87Fo0SL89ttvWLduXbPWV1BQgG+++QZjxoyBsbExAMDX15ebP3XqVAQHB0MoFMo8pkVE4PF43H9rqxmXg4hkphNRvWN2nDhxot5HbUNDQ6Gnp9es/QLwUmVbgyLHx2JrPkWOj8X2fJVJt5Bz7i90nPQetEbVHfNC3vExbVebSTCqqqowcuRI7Nq1C9bW1jA2NoZEImnWurKysrBu3To4ODhg6tSn4+vn5eUhISEBY8eOBfA0KeDz+dDR0UFhYSFXtqioCFpaWtDQ0EB5eTmkUimUlJRkWi20tbVRVFQEHR0dSCQSVFRUoGPHjnXimDx5MmxtbeuNsabPyIvS09NrdtnWoMjxsdiaT5HjY7E9H1VXQfqjP6Cpg/KJ70L0TCzyju9FsWRIsbSZWyRVVVUoKipCbGwsTE1NUVRUBLFY/MLrEYlE+PrrrzFnzhwuuQAAFRUV7N+/Hzk5OSAinD59GhYWFujatStUVFSQlJQEAIiMjIRQKISysjIMDQ0RFRXFTa8ZulwoFOLixYsAgKioKBgaGkJZuW4up66uDl1d3Tp/DMMwrYFOHgYe3YfSvMXgqb0h73CYdqbNtGBMmDABH3/8MaytrdGjRw8sXrwY77777guvJyIiAsXFxfjzzz/x559/AgCGDh2K999/H25ubtiwYQOqq6thYGDAJSAeHh7YunUrRCIR+vTpAweHp8+Hu7q6IjAwEEeOHEGXLl2wdOlSAMCcOXMQGBgILy8vqKurw8PDo4VqgWEYpmVQVibo5CHwLEaDZzpM3uEw7RCPnu0woMBqbkcAQElJCTp16iTniF4ddouk9bHYmk+R42Ox1UVSCaTrvYHcx1D6Kgi8Tp3rXU6R664+7BaJYmkzLRhPnjxBZGQkKioqADxNNrKzs+Hp6SnnyBiGYdoWOhsG3EsGz3X5c5MLhnlZbSbB2LhxI1RUVPDw4UOYmJjg5s2bMDQ0lHdYDMMwbQplZ4GO7wfMLMGzGCXvcJh2rM108szLy4Ovry+EQiHs7e2xdu3aNtV0xzAMI28klUC6ezMgUIHS3MXsTanMK9VmEoyawa66d++OBw8eQFtbm42OyTAM8wLobBiQmgje+67gaWrLOxymnWszt0g0NDQQFhYGfX19hIaGQk1NrVmPqTIMw7yOKC0JdGwPILQCz3qMvMNhXgNtpgWj5o2nhoaG6Nu3Lw4dOoS5c+fKOyyGYRiFR2UlkG7/AdDUgZKTJ7s1wrSKNtOC0bFjR+6x1ClTpkBTUxNDhw6Vc1QMwzCKjaRSSEN+BooKoOS9Abw36o4qzDCvQptpwdi+fTuuX78OAODxeEhKSsKvv/4q36AYhmEUGBGBDu0C4q+B954TeH0GyDsk5jXSZhKMlJQUfPrppwCAzp07w8vLC7dv35ZzVAzDMIqL/j4MCg8Db9xU8MZNbbwAw7SgNpNgVFdXyzw1IpVK5RgNwzCMYpNeOgM6thc8y9HgzXZh/S6YVtdm+mCYm5tj3bp1GDlyJHg8Hi5fvgxzc3N5h8UwDKNwKP4aaG8QMGgIeE5LwVNqM78lmXakzSQYjo6OOHXqFGJiYqCkpARLS0uMHz9e3mExDMMoFEq/C+m274CefaHkvhK8et7kzDCtoc2ceUpKSpg0aRImTZok71AYhmEUEuU8hjRgLdBZG0qe/uCpqsk7JOY1xtrNGIZh2gGqroJ02/eAVAKlpWvA09CUd0jMa44lGAzDMO0AHdsLZKZCaYEneN3Ya8sZ+WMJBsMwTBtHN6+DzvwBnq0DeObW8g6HYQC0oQQjKysLERERICJs3LgRHh4euHXrlrzDYhiGkSsqLoQ0ZBPwVi/wZjnLOxyG4bSZBGPbtm1QUVFBbGwsCgoKsGjRIhw4cEDeYTEMw8gNSaWQ7toEVIqg5PYZeCod5B0Sw3DazFMkVVVVGDlyJHbt2gVra2sYGxtDIpE0qWx5eTn8/Pzg7e0NXV1dJCQkYM+ePRCLxRg+fDjmzJkDAMjIyMCWLVsgEolgZGQENzc38Pl85OXlISAgAMXFxdDT04OnpydUVVVRVlaGzZs3IycnBxoaGli2bBk0NTVRXV2N4OBgpKenQ0VFBZ6ennjrrbdeZfUwDPMaovDjwJ048OYtAe+tnvIOh2FktJkWjKqqKhQVFSE2NhampqYoKipq0uvaU1JS4O/vj0ePHgEAxGIxgoODsXLlSmzcuBFpaWmIi4sDAAQEBMDZ2Rk///wziAgREREAgB07dsDOzg6bNm1C3759cfjwYQDAwYMHYWRkhI0bN2LcuHEICQkBAJw8eRIdOnTAxo0bsWDBAgQFBb2KKmEY5jVGmWmgo3sBc2vwRk2UdzgvjYjw36MqVFeRvENhWkibSTAmTJiAjz/+GIaGhujRowd8fX2bNCZGREQEXFxcoK2tDQBITU3Fm2++CV1dXfD5fIwcORJXrlxBbm4uxGIx9PX1AQC2tra4cuUKqqurkZiYCCsrK2761atXAQCxsbEYMWIEAMDGxgY3btxAdXU14uLiMHLkSADAwIED8eTJE+Tl5bV4nTAM83qiyoqnr1/v1BlK8z9pF8OAF+VLcO1SGQryqhtfmGkTlAbl8gAAIABJREFU2swtEjs7O4wfPx5K/z/k7Xfffce9vr0hixYtkvl3QUEBNDX/93y4pqYmCgoKUFhYKDNdS0sLBQUFKCkpgZqaGvh8Pjc9Pz8fAFBYWAgtLS0AAJ/Ph5qaGp48eYKCggJues028vPz0aVLF5lYysrKUFZWVidmXV3dRveLYZjXF4XuAnIeQclrLXjqjX8OtgXZWVXg8QAtHb68Q2FaSJtJMCoqKrB//35kZWXBy8sLBw4cwPz586GqqvpC6yGiOtk+j8eDVCqVmV6zXH3L1yQ5RLJNeUQEJSWlOtNrtvGsEydOcLdbagsNDYWeXvOfY3+Zsq1BkeNjsTWfIsfXnmITXbmAvMhT6PTufGiOtX9FUf1Pa9XdpbOp0Ouhjl69e7TK9phXr80kGLt27YKWlhaKi4shEAhQXl6OrVu3YunSpS+0Hh0dHRQVFXH/LioqgpaWFnR0dFBYWFhnuoaGBsrLyyGVSqGkpCTTaqGtrY2ioiLo6OhAIpGgoqICHTt25LbRvXt3bl01t2hqmzx5MmxtbeuNs6bPyIvS09NrdtnWoMjxsdiaT5Hja0+xUXEhpJu+Anr2Q9n4d1D+ivertequtESCogIxevTiv9T2FDmRfB21mT4YGRkZ+OCDD8Dn89GhQwd4enoiIyPjhdfTv39/PHr0CNnZ2ZBKpbh8+TKEQiG6du0KFRUVJCUlAQAiIyMhFAqhrKwMQ0NDREVFcdPNzMwAAEKhEBcvXgQAREVFwdDQEMrKyjLTk5KSIBAI6tweAQB1dXXo6urW+WMYhnkWEUG6OwCorICSqxd4ygJ5h9RisrOqAADd3mo/+8S0oRYMpWdeN1zTovCiVFRUsGTJEvz4448Qi8UQCoVcB04PDw9s3boVIpEIffr0gYODAwDA1dUVgYGBOHLkCLp06cK1msyZMweBgYHw8vKCuro6PDw8AAD29vbYtm0bvLy8IBAI8Mknn7zMrjMM83/s3Xl8VPW9x//XOTOZTCYL2ckGSSAEwpqwr4qIKCJu1YpX7EWLeFvF6q22/d1eWlFbqdW2FhHttSr6+6lFUFlFBIEYCShrICFAgJCQQPZ1MpntfH9/DBlB0GoIM2fC9/kgj0nOLHnPd8Kcz3zP93y/EiLvUziwC2XWAyiJvfwdp0udqXASEWnAEhown3ml70ERFxswoEPLli3DYDCwa9cu5syZw4YNG4iPj+f++7vnzHXyEInvyWydp+d83SGbqDmDtvAXkN4P9bGnUDrx4aozfNF29naNjauayRwUTP/Bl7b6qzxEoi8BUy7ec889mM1mLBYL7733HqmpqcyePdvfsSRJki4r4XZ7ZutUFdQ5v/BZceErVZWewyMJ8vBItxMwh0iMRiN33HEHd9xxB06nk6amJkwmk79jSZIkXVbiw7ehpAhl7i9RYuL8HadLOR2C0hIHIRaFiEh5emp3EzCl8Jdffsnrr7+OzWbj0Ucf5YknnmD9+vX+jiVJknTZiH07EZ98gHLVDahjrvZ3nC7VbtPYvqWV5kY3A7NDusVkYdL5AqbA+PDDD5k6dSo7d+6kX79+LFmyhNzcXH/HkiRJuixEzRnPKqm9+6LMmuvvOF2qpdnNF5tbsba6GT0plKResje6OwqYAgOgd+/eFBQUkJOTg8ViueiEVpIkSYFOVJShPff/AKD+169RgrrPDvj0KQd5n7bgcgnGTQ4jPlGOveiuAqbAUBSF7du3s3//foYNG8aePXtkl5okSd2OKDmE9txvQAjUJ/6IEpfg70hdQghB8QEbu75oIyzCwFXTwomKCZhhgFInBMyr+5Of/IT333+fu+++m8jISD788EPmzJnj71iSJEldRhw+gPb3hRAZi/rok92quCjYZaPsuIPefUwMHh6CwSA/IHZ3AVNgDBgwgAULFnh/fvrpp/2YRpIkqWuJkkNoi5+GmJ6ojz+DEhH17+8UADRNsP+rNk6VOsnICmbAELPsfb5CBEyBceTIET766CPa29s9U+ZqGtXV1SxdutTf0SRJki6JKD3q6bnoEe1ZIbW7FBduwZ6dbZwud9J/sJnMQT9scUopsAXMGIxXXnmFzMxMbDYbkyZNIiQkhDFjxvg7liRJ0iURdTVof38KQsNRf/kMSuSFCyMGIpdL8NUXVk6XOxmYLYuLK1HAFBiKonDrrbcycOBAkpKS+O///m8KCgr8HUuSJKnTtHYb2kvPgMuF+sjvUaIvXBQxELlcgp25rVSfdjFsVAh9+8vi4koUMAWG2ez5A+3Zsyfl5eWYTKZOLXYmSZKkB0LTqP/L76HiJOq8x1ESU/wdqcscK26nvsbN8HEWevcJ9nccyU8CZg+dkZHBX//6VwYPHsyaNWt46623MBjk1LKSJAUm8cFb2L74DOWOOSiDR/g7TpextWmUFNtJ6hVEcu/uM3+H9MMFTIExZ84cZsyYQVJSEnPmzEEI4V02XZIkKZBom1YhPvmA0BvvQLnuFn/H6VKHD7SDgKyh8rDIlS5gCoyGhgbv1OAJCQlUVVVhsVj8nEqSJOmH0XZuQ/zrnzB8PFH/9US3OmWzqcFFeamD9MxgLGGyh/lKFzAFxpIlS0hKSgIgNjaWQYMGyVNUJUkKKGL3F4g3/gaZg1Hn/jdKNzrM63IJDuy2EWRS6Jclx11IAVRgNDc3c+ONNwJgMpmYMWMGDQ0Nfk4lSZL0/WhffY72jz9Deibqw//brdYXcTo9Z4001LsZMiKEIFPA7FqkyyhgJtrSNI36+nqioz3niDc2Nl7SYmebN29mw4YN3p+rq6u56qqrsNvtFBcXExzsqcDvvPNORo8eTUFBAW+99RYOh4Px48cza9YsAEpLS3nllVew2WxkZWXxwAMPYDAYqK2tZfHixTQ1NZGUlMQjjzziPRNGkqQri/ZVHuL/XoB+Wajzf4diDvF3pC7jsGvs2GaludHNiLEWkuTATumsgCkwZsyYwa9+9Suys7MBOHDgAPfee2+nH+/aa6/l2muvBaC8vJw///nP3HnnnSxcuJCFCxcSFfX1THoOh4OlS5eycOFCYmJiWLRoEXv37iUnJ4fFixfz4IMPkpmZydKlS9m8eTPTpk3jtddeY9q0aUyYMIEVK1awYsUKZs+efWmNIElSwBElhxCv/wX6DvDMdRHcfT5oCCHY92UbLU1uRk0MpWeSXBlV+lrA9GNNmTKFBQsWkJaWRt++ffntb3/LxIkTu+SxX3vtNe6++26Cg4Opra1l6dKlPP744yxfvhxN0ygpKSExMZH4+HgMBgOTJk0iPz+fmpoaHA4HmZmZAEyePJn8/HxcLheHDh1i7Nix3u07duzokqySJAUOUVuF9vIfIToO9aH/6VbFBcCpUgdVlS6yhpplcSFdIGB6MABSU1NJTU3t0scsKCjA4XAwbtw4qqqqGDx4MHPnzsVisbBo0SI+++wzzGYzkZGR3vtERkZSX19PQ0PDedujoqKor6+npaWFkJAQ7zwdUVFR1NXVXfC7rVYrVqv1gu3x8fFd+hwlSfI90dbqWbzM7UKdvwAlLMLfkbqUrU3j4F4b0XEG0jPloE7pQgFVYFwOmzZtYsaMGYBnltAnnnjCe9306dPZtm0bY8eOveBUMkVR0DTtvO1CCBRF8V6e62Kzjq5bt44VK1ZcsH358uXeM2Y641Lu6wt6ziezdZ6e8/k6m9Zmpeb5/8FRXUncwr9jzh79rbfVc7vBxfMJIVj/YRmgcP1N6UREynEX0oWu6ALD5XJRVFTEz3/+cwDKysqorKz0HtoQQmAwGIiJiaGxsdF7v8bGRqKiooiJiTnvTJaO7REREbS1taFpGqqq0tDQcN6Yjg4zZsxg8uTJF81WWVnZqeeUlJTU6fv6gp7zyWydp+d8vs4m7O1oLz4Jx4pR/+s31MenwLf8fj23G3x7vlOlDk6dbGPI8BBa22ppbfNDuIvQe7F2pdH9GIw//vGPAKxfv77LH/vkyZMkJiZ6z+4QQrBs2TJaW1txuVxs2rSJ0aNHk5GRQWVlJWfOnEHTNPLy8sjJySEuLg6TyURxcTEAubm55OTkYDQaGTBgANu3b/du7xiceq7Q0FDi4+Mv+JIkKTCJ9jbPYZGSYpS5v0TJGevvSF3O6RQU7bcRGW0gNUP2XEjfTvc9GKdOnSIvL4+PP/6YmJiYC66/lCXbq6qqznvM1NRUbr31VhYsWIDb7WbMmDHegaQ///nPeeGFF3A4HOTk5Hh7OebPn8+rr76KzWYjPT2d6dOnAzB37lyWLFnCypUriY2NldOaS1I3J1qa0f6+EMqOodz/KOqoSf6OdFkcKWzH3i4YPTGkW81CKnU9RVzKZBI+sHXrVnJzcykpKaFv374XXP/73//eD6kuP3mIxPdkts7Tcz5fZBP1tWh//R3UVaM++CuUYd8+5sLX2S7FN/O1NLnZ9kkLvdJNDBulv6Ua5CESfdF9D8bkyZOZPHkyy5Yt4z//8z/9HUeSJOk8ovo02l8WQFsr6qNPomQO9neky8La6mZ3vhWjUWHAkO51uq10eei+wOhw7733smrVKvbt24fL5WLYsGHcdtttcsl2SZL8RlSWof3ld+B2ov7yGZTUDH9HuizOVDjZu9OKoiiMGG8h2Kz74XuSDgTMX8m7777LwYMHmT59OjfddBOHDx/m7bff9ncsSZKuUOLUCbQ//w8gUB9/tlsWF5omKD5g46s8K6FhBq66Loy4BDmhlvT9BEwPxr59+3j22WcxGj2Rhw8fft6cFZIkSb4iTpWivbAAjEGoj/8BpWf3O/bvcGhsWFVOeamdXukmhowIwWCQgzql7y9gCgxN07zFBUBQUJA8PCJJks+JipNoL/yvp7h44g8o8d2vuKipclLwlY12m8aQESGk9jXJM0akHyxgCoy0tDTefPNNbrjhBhRFYcOGDV0+bbgkSdJ3EQ11aH/7PRiNnp6LblZcOOwaRfvbKT/hIDRMZeadaWg0/vs7StJFBEyB8dOf/pQ33niDBQsWIIRg2LBh3H///f6OJUnSFULY29FeegZsNtTf/KlbHRbR3ILSEjtHiuy4nIKMrGAyB5pJSLJQWSkLDKlzAqbAsFgsPPTQQ/6OIUnSFUhoGtrrf4XyE6gP/xYlJc3fkbpMQ52LPTvaaGvViO1pZFB2CBGR8vCzdOkCpsCQJEnyByEE4v3XYU8+yo9/ijJ0lL8jdQkhBCePOTi414Y5RGXMVaHEJ8ozRKSuIwsMSZKk7yDWLUdsWo1y7UyUqTf7O06XcDo0DuyxUXHSSXyikZwxFkzBATNrgRQgZIEhSZL0LbSt6xGr/j+Usdd4ei+6wZkU1aed7P+qDXu7oP9gM/0GBneL5yXpT8AUGJqmsWbNGjmTpyRJPqHt2IJ451UYNhrlP+ejqIH9Cd/a4qb4YDuVZU7CIlRGTQglMiZgdgFSAAqYv6533nmHkydPMn36dIQQbNq0ibfffps5c+b4O5okSd2M2LMd8caL0H8I6rwnUIwB81Z5AadTUFxg4+QxB6oK/QYG02+gWU6aJV12AfO/Zv/+/XImT0mSLjux/yu0fzwP6ZmoD/0WxRTs70id1ljnYveONtqsGml9TfQbaMYcEtg9MVLgCJgCQ87kKUnS5aZ9vhHx/74MvfqgPvI7FHOIvyN1WtlxOwW7bJhDFMZfE0ZMXMC83UvdRMD8xcmZPCVJulyEEIjV7yLWvgeDclD/69coZou/Y3Waw65RuNdGdJyRkRMsmEyy10LyvYApMH7605/y+uuvs2DBAjRNIzs7W87kKUnSJRNOB2LZYsTObSgTrkWZ/VBAj7kAOHHUjssFg3NCZHEh+U3A/C+yWCw8/PDD/o4hSVI3Ipob0V7+IxwrRrl1NsqNdwb8KZtOp+DEEQcJyUFyRk7Jr3RfYLz88svfep2iKPzsZz/r1OMuXLiQpqYm7ziOefPmUVVVxcqVK3G73dx4443ccMMNABQUFPDWW2/hcDgYP348s2bNAqC0tJRXXnkFm81GVlYWDzzwAAaDgdraWhYvXkxTUxNJSUk88sgjmM3mTuWUJOnyEPU1nlVRG+pQH/wVysiJ/o7UJUqP2nE6Bf0GBu7gVKl70H2B0atXrwu2tbS0sG7dOuLj4zv1mEIIKisrefnll70FRn19PX/729/405/+hNFoZMGCBQwePJj4+HiWLl3KwoULiYmJYdGiRezdu5ecnBwWL17Mgw8+SGZmJkuXLmXz5s1MmzaN1157jWnTpjFhwgRWrFjBihUrmD179iW1gyRJXUfUVaM9/1uwtqD+8hmUvgP8HalLuJyCY4ftxCcaiYzW/du71M3p/i9w5syZ5/1cUFDAkiVLmDRpEvfdd1+nHrOyshKAZ555htbWVq699lrMZjODBw8mLCwMgDFjxrBjxw4GDhxIYmKit5iZNGkS+fn5pKSk4HA4yMzMBGDy5MksX76cKVOmcOjQIe8ptJMnT+bJJ5+8aIFhtVqxWq0XbO9s4SRJ0r8naqs8xYXNivrY0yjp/fwdqUs01rvY92UbTocgc6DsMZX8T/cFRge3280777zD1q1beeCBBxg7dmynH8tqtTJkyBDuv/9+XC4XCxcuZNy4cURFRXlvExUVRUlJCfX19URGRnq3R0ZGUl9fT0NDw3nbo6KiqK+vp6WlhZCQEG/PSFRUFHV1dRfNsW7dOlasWHHB9uXLl5OU1PmloC/lvr6g53wyW+fpOV9HNs3WRvUzjyHabcQ/+yqmDP/3XFxqu7lcGrvza9i/u5EQi5EbbkkmtU94F6XT9+sq6VtAFBinT5/mxRdfxGw289xzzxETE3NJj5eZmenteQC45ppreOutt7j99tu924QQKIrivTyXoihomnbe9u+6vfotUwzPmDGDyZMnX/S6jl6WHyopKanT9/UFPeeT2TpPz/k6sglNQ3tlEZSdQH3099RaIsDPmS+13arPODmwy0abVaN3uomB2WaCTC1UVrboIp+vyWJIX3RfYGzZsoW33nqLmTNnnlcAXIri4mKcTidDhgzxbouLi6OxsdH7c2NjI9HR0cTExFywPSoqipiYGBoaGi7YHhERQVtbG5qmoaoqDQ0N5/WMnCs0NJTQ0NAueU6SJH03sfZfsHcHyl0/RRmY4+84l8TpEBzc28apUieh4SrjrgklNl4utS7pi+4LjFdeeQVFUfjoo49YtWqVd3tHT8GyZct+8GNarVaWL1/O008/jdvtZtu2bcyfP5/FixfT3NxMcHAwO3fu5MEHH6R3795UVlZy5swZ4uPjycvL45prriEuLg6TyURxcTEDBgwgNzeXnJwcjEYjAwYMYPv27UycOJHc3Fyys7O7skkkSfqBtM83Ita8izJuCsq1gb3kem21k30722i3CbmuiKRrui8wXnrppS5/zBEjRnD06FF+/etfo2ka119/PQMGDODuu+9m4cKFuFwupkyZQkZGBgA///nPeeGFF3A4HOTk5HjHf8yfP59XX30Vm81Geno606dPB2Du3LksWbKElStXEhsbyy9+8Ysufw6SJH0/1q0bEG8vgcHDUX7yUMDOc+F0aBwqaOfkMQehYSoTrg0lSq6GKumYIoQQ/g4hXUiOwfA9ma3z9JpP7P8S7eVnIWMA6iNPogTra26I79tup085OLDbht0uSO8XzIAhZozGy18o6fV1/TZyDIa+yPJXkqRuSZw8hvaPPxPUtz/uhxforrj4PtxuQdE+G6UlDiIiDYyeFCLnt5AChvxLlSSp2xGNdWgvPQ1hEcT97i9UtTv8HekHs7a62ZPfRmO9mz6ZwWQNNaPKsRZSAJEFhiRJ3Yqwt6O99Aew2VB/swhDdKzfT0f9IYQQnCxxUFRgQ1Fg5AQLiSkmf8eSpB9MFhiSJHUbos2KtvgpKDuO+tBvUVLS/R3pB2mzutn/pY3aahdxCUaGjbIQYpGroUqBSRYYkiR1C6KlGe1vv4eKk6gPPoEybJS/I31vQghOHnNQtN8GwNCRIfTuYwrYM14kCWSBIUlSNyDqqtFeXAi1VagP/Q/KkJH+jvS9Oewae3e2UX3aRWxPT6+FJVT2WkiBTxYYkiQFNHGyBG3x0+BwoP7iSZT+g/0d6XurqbKRu7EFe7tg8PAQ0jJkr4XUfcgCQ5KkgCX2f4X2j+cgvAfqfz+NktTb35G+t4oyB/u+LMUUDOOnhMlJs6RuR/5FS5IUcIQQiE9XIVa8Ab37os5fgNLj4mv+6NHxw+0U7msnMdnCkFFGgoPlIRGp+5EFhiRJAUW4nIh3XkV8vhFGjEe977GAmUTL7RYUF7Rz/IidhJQgbrytN9XVZ/wdS5IuC1lgSJIUMERzA9rSRVByCGXGj1Fu/g8UNTA+/VdVOjm4x7O0elqGicE5IRiNgZFdkjpDFhiSJAUEUXrUs66ItQVl3q9QR030d6TvpbnRTdF+GzVnXISFq4y9OpS4BLm0utT9yQJDkiTdE4f2oy35A4RFoP76Tyi9+/g70r/V3Ojm2OF2TpU6CQpSGDjMTHq/YDndt3TFkAWGJEm6JvZ/ifbKn6BnEupjT+l6MKemCSrLnJSW2Gmoc6Oq0Ld/MBlZwZjkQE7pCiMLDEmSdElobsTmtZ4zRVIzUH/xe5TQcH/Huii3W1BZ5uBokR1rq0ZYuMrAbDO90kyysJCuWLLAkCRJd0RFGdqyv8OJIzB0FOrcX6KEWPwd6zyaJjhT4eR0uZOq007cLoiINDBqYig9k4xywizpiicLDEmSdEM4nYj17yM+XgEhIShzf4ky+ipd7ayFJqgoc3KkqB1ri4YpWCG5t4mkXkHE9pSFhSR1uGILjPfff5/8/HwAhg8fzuzZs3n55ZcpLi4m+Ow59XfeeSejR4+moKCAt956C4fDwfjx45k1axYApaWlvPLKK9hsNrKysnjggQcwGAzU1tayePFimpqaSEpK4pFHHsFsNvvtuUpSIBBHi9DeegnOnEIZczXKXXNRwnv4O5aXyykoO+HgxFE7ba0aET1URk6wkJAUhKLKokKSvumKLDAKCgooKCjgueeeA+CPf/wjX375JceOHWPhwoVERX09iMzhcLB06VIWLlxITEwMixYtYu/eveTk5LB48WIefPBBMjMzWbp0KZs3b2batGm89tprTJs2jQkTJrBixQpWrFjB7Nmz/fV0JUnXhK0N8cFbiK3rISbeM9Zi8Ah/xzpPc6ObLz5rweWEqBgDA4dZSEgOkr0VkvQdrsjRR1FRUdx7770YjUaMRiPJycnU1tZSW1vL0qVLefzxx1m+fDmaplFSUkJiYiLx8fEYDAYmTZpEfn4+NTU1OBwOMjMzAZg8eTL5+fm4XC4OHTrE2LFjvdt37Njhz6crSbokhEDs3YH25MOIbR+jTL0ZdeFLuisuAMpPONDcMHFqGBOnhpOYIhclk6R/54rswejVq5f3+9OnT5Ofn89TTz1FYWEhc+fOxWKxsGjRIj777DPMZjORkZHe20dGRlJfX09DQ8N526Oioqivr6elpYWQkBAMBoN3e11d3UVzWK1WrFbrBdvj4+O76qlKki6J6kq0916DA7sgORV13q9Q+g7wd6xvVXXaSUy8US5IJkk/wBX9v6W8vJxFixYxe/ZskpKSeOKJJ7zXTZ8+nW3btjF27NgLPqkoioKmaedtF0KgKIr38lzqt0xlvG7dOlasWHHB9uXLl5OUlNTp53Up9/UFPeeT2Trv3+UTmoZ9/5e0rluBbWcuSrCZHnMfI2zmXSjGy/tWdClt19Rgx9rSSPbIeJKSorswlUegv66S9G2u2AKjuLiYF154gTlz5jBhwgTKysqorKz0HtoQQmAwGIiJiaGxsdF7v8bGRqKiooiJiaGhoeGC7REREbS1taFpGqqq0tDQcN6YjnPNmDGDyZMnX/S6ysrKTj2vpKSkTt/XF/ScT2brvO/KJzQN9mxHW/svqDgJYREo19+GMuUmWiJjaKmu9lu27+P44XYAzBYrlZXtXRULCOzXVY9kMaQvV2SBUVtby5///Gcee+wxBg8eDHgKimXLljF48GDMZjObNm3i6quvJiMjg8rKSs6cOUN8fDx5eXlcc801xMXFYTKZKC4uZsCAAeTm5pKTk4PRaGTAgAFs376diRMnkpubS3Z29kVzhIaGEhoa6sunLkk+JcpPoP3zL57CIiEZ5b5HUUZNQgkKnLU4qk67CItQsYQZ/B1FkgLKFVlgrFmzBqfTybJly7zbrrvuOm699VYWLFiA2+1mzJgxTJzoWUzp5z//OS+88AIOh4OcnBxvL8f8+fN59dVXsdlspKenM336dADmzp3LkiVLWLlyJbGxsfziF7/w/ZOUJD/TdmxBvLUEQsM881mMmoiiBtZO2ukU1FW76NM/MJaDlyQ9UYQQwt8hpAvJQyS+J7N13rn5RM0ZxNp/IbZvhv5DUOc9jhLhv/VDLqXtKssd7N7exvgpYcTEdf3nsUB6XQOBPESiL1dkD4YkSV1PnDyG2Pgh4qs8MKgoN/wI5dbZKIbA6rU4V3WliyCTQlRM4D4HSfIXWWBIktRpQtNg/5dU/+1jtMK9EByCMu0WlKk3o0TG+Dtep9jbNc5UOKk+46K60klCShCqnKlTkn4wWWBIkvSDCc2N2L0dsfZfUFmGKz4R5c77USZeh2IJvIHLQgiqT7soO+6gqtKJEGC2KKSkmcgcJKf5l6TOkAWGJEnfm9DciK/yPIXFmVOQ2Atl7i9JvPlOTldd3tNNLwdNE1ScdFJS3E5rs2fhsvTMYHqlmQjvocrZOiXpEsgCQ5Kkf0u0tSJ2bkN8thbOVEByKsq8X6GMGI+iqiiGwHorcbsE5ScclBS3Y2sThPdQyRljIalXEKpBFhWS1BUC611BkiSfEi3NiI/eRuzYAg4H9O6L+l+/hpxxKN8yQ62euZyC0mN2jh+2Y28XRMUYGDLCTHyiXGZdkrqaLDAkSbqAEAKRvwXx/j/B1oYyYSrKVdejpGb4O1pZZuZfAAAgAElEQVSntLa4qTjp4MRRB06HILankeHjgomJk4WFJF0ussCQJAkA0W6Dor2IQs8XddXQdwDqvQ+hJKf6O94PZm11U1nmZPtnx6irsQPQM8lIv4FmuWiZJPmA/F8mSVcw4XR4zgbZlQeFe8HlhBAL9B+Kcss9KGOuDqhDIR1ngxwpbKex3g1Az8QQBmabSeplIsQSOM9FkgKdLDAk6QojnA44cRSx/0vE9k3Q2gLRsShX34CSMw76Drjsq5t2NSEETQ1uDhW0U1vlIjRMJWuomaTeJjL6pQTUbJSS1F0E1ruIJEk/mGhvg6OHEEcPIo4UwskScLnAYIDsMahXT4f+QwKqpwI8RUVdtYtTpU5qqpy02wRBJoXBOSGkZpjk5FiS5GeywJCkbkY4nXDqBKLkEOLALjhSCO6zBUVqBsq1N6P0GwgZWSih4f6O+4NpmqDmjIujRe001LkJClKITTASn2AkITkIU3BgFUqS1F3JAkOSApgQAk6VIg4XwKmTiFOlUFHq6aEAz0RYU2eiDBoOfQagBAfmqqC2No26ahfVpz1TeDsdghCLwpARIfRKN2GQc1fojiYEbU4Nq8NNq0Ojxe6mxe6msd1Fvc1FY7uLpnY3zXY3Vocbm1NDAL+/phd9ouXsqd2BLDAkKYAIhx1OlyNOn4LyE4h9O6D6tOfK8B6QkubpoUjPhPR+KNFx/g3cCS6XoLnRTWOdi8Z6N/V1bmxWDQBTsELPJE9PRc9EOSmWrwghsDo06ttdNNo8hUGT3UWz3U1zu5sWh5tWu5sWh6egaHG4aXN4CoaLMaoQaTbSw2wkIthAQlgQIUEqEcFG4kKDfPrcpMtHFhiSpGNCc0P1GaxFe3Bv2QBFezwTXoHnkEf/ISjX34YydFRALi7mdglamt001nu+mupdtDRriLN7JrNFISraSJ/MYGLiDET0MKDIsRU/WF2bkwabm3aXRrtLw+7SsLsFNqeG1enpPTh3W4vdUyTYtVKsdic2p4bDffFyIdykEh5sIDzYQKTZQEqEiTCTSqjJQJjJQKhJJczkuT7cZCAyxEi4SU7DfiWQBYYk6YTQNKg9gzhxFI4VI44fhsoycDqoB4iM8Ux41X8oJKZAXCJKUGB82tPcgsYGN80NbqytGlarm9YmDatVo+NjbpBJITLaQM/kICKjjURGGzCHyPEUl6Kuzcn/u7+WLcebvrU3AcCoKpiNCsEGFXOQSrjJQKwliJiIUITTjiVIJSrEePbLQI9gIxFmT8FgkAWf9C1kgSFJfiA0N9TXwskSxLFixIkjUF4KdpvnBsFmSOuHMnk6JKcSP3wMNeYw3X/q0zSBrU2jrVWjtUWjtdlNc5Ond0LzTEuBaoDQUJWISAPJqUGE9zAQGWUgJFR+qv0uQggcboHVqWFzarQ5z/ZIOIW3Z8Lm0mhzarTa3TTZ3Xx5qgWXBrdkRTMoPgSzUSXYqHouDQohQSqWIJUgw8ULuaSkJHmKr9RpssCQpC4kHHaoq4HmBkRTAzTUQX0NoqEW2m2er9ZmqK8B99k9rjEIUvuiTLgWeqWj9O7rWUzMYPA+rikpCcWPb/SaW9Bm1bC2atjaNNptGnabwG7XsLcLhFaCzebE4RCc+1HZGAThEQZS+3oOcURGGzGHKFdEIdFRENhcnoLA5i0MNO82U4WLmoZG7C6B3e05TNHu9Nyn/Wyx0Ob0jGewOt24tO/3u0OMKuHBKiOSwrg3O47EcNPlfbKSdBGywLiM8vLyWLlyJW63mxtvvJEbbrjB35GkSyBcLmhrgZYWTwHR3AgNtVB9GlF92jPYsqH2wjuGWCAyBkLDwBKKEtsTRk6E2J4ovdI9RYXRN4c6hBC43eB0CJwOgcslcLs8ly4X3u/dLoG9XWBt9fRGtLVp5xUOKBAcrBBsVjAFq/ToYcbl9gzCtISqWMIMhIapuiwmNCFwaQKn23PpcHfs3IVnB392LILD5Rl30NE70H72+o7bOtye6zu+nO6vb9PRm6B913GJc6gKnsMTRoVgo0pIkEqIUSXSbCA53ITFpBIa5BnXYAk6e/3Z24QEeXolQs5+mYNUjPKwhaQDssC4TOrr63n33Xf505/+hNFoZMGCBQwePJiUlBR/R7uiCSHAZoU269c9CrY2RFsrreZgtKoznm0tTYjmBmhuhOYmaG3y3OdiwntAfCLKgKEQn+gpHCKjoUcU9IhGsYR2KqfbBW63QNOgqdFBS7MboXm2uc8WBC7nuUXC19e53Zy99Gx3OgQOu4bDIbyHKv6dIJNCaJhKZIznUEZouKdoCLGoBJsVVFVBEwK3JojvmcipykrcAtyaZ8fd5HZR1+z5XhPgFgK35rneefY2bk3gOme7W3h2/B2XrrO37fjecx8893cLHJqG0y28P3c87rn31TiGw+n2Xvd9d/rfpCp4Dy0EG1VMBgWTwXMZYlSICA7yFgjmc3b2IecUDBaT+nWBYFRJS0mivqYao4ruCjFJulSywLhMCgoKGDx4MGFhYQCMGTOGHTt2cMcdd3hvY7VasVov3GnFx8d36nfa2x2s/2AHLa0X2RGKC745/zrxze3iojf9ruvEeY8hvvGtAAQhpiJsNts3fp/y9Q014Rns2HF/wfnfd/wsBLjdntsKDc9e4+vHFG43wuX0zAfRsdntRjjsCE14f6VA8XwpKkJRQVERihmMEWhBfSHWjEgKBoMJYTSB0YAwBIHBiDAYwRiEUA1nn//ZCC0gmjvy2gE7ouNZnhNTCFA0zxcaKEKBc7YpnLvDaf6W1+J8GgJN9VwKBdyKQFMELgWcioYzSOAwaTgQuBSBE4FLaDgBJ57tDk3DKc4+Vgu4mz07ZU0TuIWnB0A7WxR83eJHvle+zjKqCkZVIUgFg6pgUBXPDl5VMRoUglSFIIOC2ej52XNbz7YeYWE42tswnN1mNCgYFc91xrOP01EweMYoeAY7ms5eenoHPLft6iIg3BxEizzVVuqmZIFxmTQ0NBAVFeX9OSoqipKSkvNus27dOlasWHHBfZcvX05SUtIP/p3vLvuc5voYIOIH39dXmrrywQxnv3xFgHAIvllGCe/3wvuzds73HbRzbqOdvYcLcKDhRKCBpxjA8+VUPNuEItAUxXNfxXNfTRW4z15qiud+QlVAUTCooCrK2S9QVQWD4tkpq95LFVVRMKkKZkXBcPZ2HdcbFAW1Y2eunL+9Ywevnt3pG7+x3agqGA2ebnrPTlz9+j6KZ4duNKhnd/aq9zGMZ28T1HFfo0qQqhJk0N9hlq7Umf/rvqT3fJJ+yQLjMhHf6BEQQlzwJjljxgwmT5580ft3ZuT2xClpVJxooqG+8cIr/90btKIAyoW3++bdvNdfcEXHv4v/TkUFBXpERtHU0vL19UKAonx9U4PqOc3gm+tiKIrnE/03f8e/eWrnRcCz40XxdHd3UM/+/vj4WOrq6lDPdlernsgYDJ7vVRUMiqeN1HMeQ1U8fQ2eh1bOXnZc15Hj0naQeh/Nf/F8X5db38p99uucezjOfl3ebPqg52yg/3zfJIshfZEFxmUSHR1NcXGx9+fGxkaio6PPu01oaCihoT/8+Py3MRgMjL1qsK7fEPT8hpWUFEGo2urvGJIkSd2CnMXmMhk6dCgHDhygubkZu93Ozp07yc7O9ncsSZIkSfIJ2YNxmURHR3P33XezcOFCXC4XU6ZMISMjw9+xJEmSJMknZIFxGU2cOJGJEyf6O4YkSZIk+Zw8RCJJkiRJUpeTBYYkSZIkSV1OFhiSJEmSJHU5WWBIkiRJktTlFPHNGaEkSZIkSZIukezB6Eaqq6v58Y9/THV1tb+jXJSe88lsnafnfDJb5+k9n6R/ssCQJEmSJKnLyQJDkiRJkqQuJwsMSZIkSZK6nCwwJEmSJEnqcoYnn3zySX+HkLpOUFAQgwYNwmQy+TvKRek5n8zWeXrOJ7N1nt7zSfomT1OVJEmSJKnLyUMkkiRJkiR1OVlgSJIkSZLU5WSBIUmSJElSl5MFxhVIz8NuNE3zd4TvJNuuc/ScDeTr2ll6zib5nywwrhBCCBwOBwCKovg5zfnOzaaq+vuT1DSN5uZmANxut3e7HnZKem+7DnrOBp7/E3p4PS9Gz22n52yS/xn9HUDyjVdeeQWHw0FVVRXXX389ffv2JSUlxd+xAH1nA3jppZdob2+nqamJUaNG0adPH4YOHaqLQk3Pbff6668jhKC8vJzbb7+djIwMLBaLv2N5vfvuuxiNRsrKyrjjjjtITU0FPEWbv19bPbednrNJ+iLnwbgCbN68maKiIn7zm99gMBjYv38/Z86cwWQyERcX59c31H+XTdM0v77Zb9u2jaKiIv73f/+XyMhIqqqqKC0tpbm5mcTERIxG/9Xoem67jRs3UlhYyJw5c3C5XGzYsIGGhgaSk5MJCQnx++u6fv16Dhw4wLXXXktbWxtvvvkmDoeDgQMHenszZNsFVjZJf2SB0c0JIdi9ezcJCQkMHDiQtLQ0MjIyOHbsGPv37yc9PZ3w8HCZ7VscPXoUg8FAdnY2SUlJpKam0tzczNGjR4mOjiYmJsYvufTcdpqmsXXrVoYMGcKgQYPo378/gwYNIj8/n/z8fLKzszGbzX7JBuByufj444+ZMmUKw4YNY/DgwWRnZ7N69Wry8vIYM2YMQUFBfsmm57bTczZJn2SB0c0pikJQUBC7du0iLi6OiIgIwsLCGDp0KCUlJXzxxReMHTvWL8dS9Zytg8Vi4YsvvkBVVWJiYggLCyMjI4PKyko+++wzxo4d65deDD23naIoaJpGYWEhGRkZmM1mwsLCGDduHEVFRRw8eJCRI0f6PFcHVVWxWq2UlpYybNgwAHr06MHUqVMpKCigtraWAQMG+CWbnttOz9kkfZIjdLoxu91OTU0NmZmZJCYmsn79eg4dOuQdsHjXXXfhcrm8gwRltq81NTVRXl5Oz549ycnJYf/+/ezYsYOKigoAbrnlFtxuN3a73efZ9Nx2HQNiR4wYgdPp5J///Cdnzpzxnm3wox/9iJaWFr+9ruBpvzFjxnD48GEWLVqEy+XyXjd16lROnTp13mBeX9Fz2+k5m6RfcpBnN3Xw4EHWr19PeXk5WVlZzJs3jw0bNrB69Wrvp7OTJ0+SkJBASEiIzHaOgoICVq9eTXV1NZmZmdx7771ERkaye/duysrKaG9vx2q1kpKSQkREhE+z6bntioqK+PTTT6mqqiIzM5P58+fz5ptv8sILLzB16lRCQ0O9PS7+WNvi8OHDbN26lebmZrKysnjmmWd4/vnn+dnPfsZ9991HfHw8GzduJC4uDoPB4NNsem47PWeT9E0eIumG3G43S5YsYebMmcyZM4dPPvmE06dP86Mf/Yi4uDhaW1txOBwkJCRw1113yWwXyXfXXXfxk5/8hO3bt7Nv3z7uuOMO4uPjiYiIQFEUMjIyuPXWW/2STY9t53K5WLx4MZMnT+aWW25hw4YNCCG47bbbiI2N5ejRozQ3NxMeHs69997r02wd+V588UWys7MZPXo0W7ZsISoqittuu43o6Ghyc3Opq6vDYDBw3333+TybXttOz9kk/ZM9GN1QeXk5oaGhDBs2DEVRmDlzJqtWrcLlcpGVlUX//v39Nq5Bz9kA6urqCA4O9p7q+eMf/5glS5Zgs9lITU0lJSWF4cOH+yWbntvu6NGjxMTEMH78eAAmTpzI7t27ueaaaxg+fDjZ2dmoquq3iZkKCgpITk5m2rRpaJpGamoqeXl5DBkyhIkTJ3rH0vgjn57bTs/ZJP2TYzC6mZMnT9LW1obZbPaOF0hMTMRms3kHI7799tvU19f7fGIhPWcDTxd6dXU1vXr14vTp0wBERETgdru9XeZvvPEGlZWVPs+m57Y7c+YMbreb5uZm6uvrAejbty+NjY3eUxbfe+89bDabT3N1aGxsxGg0cuLECZqbm1FVlSFDhlBdXe29zYYNG2hvb/d5Nj23nZ6zSYFBFhjdTHl5ObW1tUyfPt37abZHjx7YbDZsNhurV6+moqKC6Ohon5+vrudsAK2trRQXFzN69GgiIyMBCA4Oxm6309LSwpo1a6ipqSEpKcnn2fTadpqmUVBQgMFg4K677qK1tRWAuLg42traAFi1ahUnTpwgJCTE5z0sLpeLrVu3kpCQwJw5c7z5kpOTvd9/9NFHFBcXYzabfZpPz22n52xS4JB/Fd1M7969KSoqorW11bsjVFWVPn36sHLlSr744gsefvhhme0iMjMzvaPl4+PjATAYDGRlZfHee+/xxRdf8NBDD/klW2pqqi7bTlVV4uPjWbVqFXa7nd69ewOeUxoTExNZs2YN27dvZ/78+T7PBmA0GomMjGTp0qUIIc5ru+joaLZt20Z+fj7z5s3zeTY9t52es0mBQw7y7GZ69OhBTEwM69atw+VykZqaitFopLy8nI8++ogHH3yQtLQ0me0igoODiYyMZPXq1dTV1ZGZmYmqqjQ1NfHBBx8wb9480tPT/ZKtR48exMXFsXbtWt20XWVlJeHh4SQkJJCcnMxnn32GxWIhPj4ek8nkPRvHX69rbW0tFouFtLQ0EhMT2bt3LwkJCYSGhmI2m8nNzWX9+vU88MADfntdO9puy5Ytumo7vWeTAoMsMLqBmpoaDh06xO7du4mPjycxMZH09HSOHTtGr169MJlMBAUFYTabmT59usx2jsrKSvLz8+nTpw+KohAREcHw4cM5evQowcHBREdHYzAYiIyMZOrUqT7PdujQIZKTkwGIjIwkLS2NEydOkJKS4te2Ky8v54033iAnJ4fg4GCioqIwGAyUl5eTmZkJeD4Fh4SEcNNNN/k0W0e+5cuXM3jwYEwmE7GxsVRWVlJRUUG/fv1QFAWXy0WPHj2YOXOmT7PV1NRQWFhIfn4+aWlpxMfHYzAYKCsro3///oD/2k7P2aTAIwuMbuCFF17AZrNRXV2N1WolIyODiIgISkpK2Lp1KwMHDiQxMZHs7GyZ7RtKS0t58cUXaWlpoVevXlgsFoxGI/X19ezatYt+/foRHx/PwIEDfZ7twIED/PWvf6W1tZWcnBwAgoKCKCkp4fPPP/dr2y1evJiZM2cSHx/P0aNHOXHiBMOGDeOrr77i888/Z9CgQaSmpjJixAifZwN48cUXmTp1KsnJyVRWVlJVVcWoUaPYunUr+/btY+DAgfTr188v+Z5//nkaGhro3bs3vXv3xmg00rNnT3bt2kVubq5f207P2aTAIwuMALdhwwbq6+t5+OGHURSFDRs2UFRUxObNm7nrrrtwu93k5eWRlZXl8ymt9ZwNPAPZevToQWFhITU1NWzbto1evXpRWVlJWloadXV1bNiwgZycHJ9PICSEIDw8nKKiIioqKnj//fcZNWoULS0tjBw5klOnTrFnzx6/tN17771HTU0Nt956K0899RTNzc1s2rSJAwcOMHfuXNra2jh+/Djp6el+Gfz3zjvvYLPZmDFjBn/4wx84fvw4mzZtorCwkHnz5tHQ0IDVaiUhIcHng4lzc3OpqqriscceIy0tjVWrVrF9+3Z27NjBnDlzsFqtHDt2zC9tp+dsUmCSBUaAs1qttLa2MmzYMPLy8qiuruaBBx6goqKC5cuXc/PNN5OSkkJcXJzM9g0d63kAXH311eTk5LB48WI+/fRTpk2b5l2a3R8LmimKQkhICK2trdx9992kp6ezcOFCPv30U2699VaGDh1KRESEdzCqrwghsFqtuFwutm3bxqhRo5g1axY33ngjhYWFfPrpp4wdO5bIyEh69uzp02zgOWukrKwMi8XC9u3bycnJYfbs2dxwww3s2bOHvXv30rt3b0wmE4mJiT7PJ4SgtLSU0aNHs3LlSk6dOsXVV1/NsWPHWLt2LePGjSMqKsovbafnbFJgkgVGgFNVFYfDQVpaGn369OGGG24gNDSU4cOHU1payuDBg72TRslsF1dVVcXWrVu56aab+PLLLwkPDyc/P5+MjAzv6Hl/OXXqFAUFBcyYMYOCggIUReHjjz9m/Pjx3rEZvqQoCvHx8VRUVFBSUsKECROIjY1FURRGjBhBYWEhkyZN8uvfXM+ePdm3bx+HDh3i5ptvpkePHgCkpaVx6NAhbrnlFr+0XYdVq1Zx6NAhAO6//34SExMZM2YMhw4dYvz48X79m9NzNinwyJk8A9Tu3bu9qxtOnjwZ8Kz86XK5MBqNnDlzhqNHj/plwio9Z+vI13F2yOTJkxk7dixfffUVf/nLX0hOTubBBx/kww8/xGKx+DxbcXExBoMBm83G0KFDmTJlCn//+9956aWXSE5O5umnn+bNN9/0y6RQHa+rw+Hg5ptvJiEh4bxPs9XV1Rw5coT29na/LBVfXFyMqqoYDAbmzp3Lxo0bCQoKQtM0VFVFVVWOHTtGc3Mz0dHRfslmMplYsGABa9euZfPmzfTv358JEyZ42+7chddkNinQKcJf7/JSp33++eesXbuW4cOHc+LECcrLy3nkkUfo37+/dxBbfX0948aN8/nZBXrOdm6+ESNGcOLECcrKyvj1r3/NmTNnWLNmDU888YTPFzDrkJubyyeffEJSUhJOp5Pm5mbmzZvHwYMHyc3N5fHHH/dbtnNf1+PHj1NdXc38+fPp06cP7777LhUVFTQ2NjJ+/HhuvPFGn+c7t+3a29txOp385Cc/ISkpieXLl3Pq1CkaGxsZOXIkN998s9+y2e12Wltbuf7666mpqeHDDz8kKysLq9XKqFGjfN52es4mdQNCCigOh0P89re/FUVFRd5ta9asEbNnzxZr1qwRTqdT5OXliVOnTsls3yPf6tWrxT333COWLVsmWlpahBBCOJ1On2ez2+3i8ccfF6WlpUIIIZqamsT7778vHn30UbFs2TJRU1Pjt2zf1m6zZ88W69atE3a7XWzfvl2Ul5f7PJsQ3912mzZtEk1NTWLt2rXi6NGjusj2wQcfiEcffVR89tlnorGxUeTn54uKigqZTep25BiMAFRfX4/FYvEeR87MzGT06NGsWbOGnj17MnLkSL990tVztovl69+/P6NHj2br1q1ERUWRlJTklxHyqqpy/PhxevfuTUxMDMHBwQwcOJCUlBQKCwtJS0sjKirKb6P3v63dVq9eTUJCAiNGjPDb6/ptbZecnMznn3/OgAEDGDFihM8Pi3xbtqysLJKTk8nNzaV///4MHDjQL4eU9JxN6h5kgRFASkpKKC0tJTY2lpdeegmLxULfvn0Bz6JcdrudqqoqsrKyZLYfmM9ms1FfX8+AAQN8nq24uJjW1lYsFgv//Oc/iYyMpFevXoBncq2SkhKcTqc3ry/p/XX9rraLiorixIkTtLW1kZGRoctsNpvNL6+rnrNJ3Yc8mTmAtLe38+mnnxIVFcXvfvc7tmzZwvPPP+9dfOjUqVM0NTXJbJ3M19jY6JdsdXV1vP766yQmJnLfffexZcsW70BOk8mE3W6noaHBL9n0/rp+n7bz1+taU1Oj29dVz39zUvchB3kGmCNHjrBhwwZuvPFG4uLiWLZsGYcPH2bIkCFUVFTw5JNPepcW97WSkhLWr1+vy2yg77YrKipi7969TJo0CYfDwYYNGygsLGTEiBEcOXKEZ5991m/Z9NxuoO+2O3ToEHv27NFltsLCQvbu3ctVV12lu2xS9yALjADgcDhwu91omkZoaCj79u2jvLzcu4bCiRMn6NGjB0FBQT4/XlpbW0tsbKz353379lFZWekdce7PbAA2mw3wzN9gNpvZt28fFRUVzJgxw+/5nE6ndyZJRVH47LPPALjuuusATze2xWIhIiLCu3y8r+i53UDfbbdy5UrCw8OZNm0aDoeDbdu2oSiKdy0bf2Zrb29H0zTAc+r4p59+qptsUvcjx2Do3OHDh3nvvfc4ePAgeXl5BAUFMWLECHbt2sXWrVsZMmQI8fHxhISEYDKZfDr1cU1NDc899xxGo9G7GqXFYmHnzp3k5eX5NRt43izffPNNCgsLsVqt9O3bl/DwcPbs2cO2bdv8mu/IkSMsX76c3bt3ExERQc+ePYmNjWXLli0UFBQwcOBAEhIS6NGjB2az2We5QN/tBvpuu6KiIl577TUMBgPjxo3DYDAQExPDJ598QnFxMVlZWX5/XQ8ePEhJSQl9+vQhKSmJDRs2+D2b1D3JAkPHXC4Xf/jDH5gxYwZDhgzBarXy/vvv09zczOzZs2lsbPSOAjcajT5/o29vb2fTpk2Ul5dTUFBAeno6MTExDB8+nJqaGkpLS/2WzeVy8eyzz3LTTTcRFRXF7t27SU5Opry8nBtuuAGbzcbhw4f9ks/lcvH0009z3XXXYbPZ2LlzJ6mpqTQ0NDBt2jSamppobW31y1TWem63jnx6bruXX36ZWbNmUVNTQ8+ePYmMjMRsNjNu3DjKy8ux2+1+fV1nzpxJRkYGR48exe12M2DAgPOy+WN9Fqn7kjN56ljHstyjRo0CPCtpCiGorq7mnXfeYfz48ezYscNv+WJiYrj22msJCwujubmZ1157DaPRyNChQ5k8eTJr1671W7aamhpSU1MZO3Ysbreb5cuX8+GHH+JwOFi1ahW33nor1dXVfslWUlJC7969GT9+PNnZ2cybN4/33nsPgPDwcAYNGsSePXu8S437kp7bDfTddv/3f/9HSkoK48eP5+DBg3zwwQc89thj3utTU1PZvXu3X7J1tNuYMWMAzyDPXbt2MW7cOIKDg0lJSeHQoUMMGTLEuz6PJF0q2YOhY8HBwaxevRpN0+jXrx95eXnU1tYybdo0tm3bxjXXXEP//v19PqW1pmneqcDdbjf79+/n3nvvpaKigi+//JKIiAjGjBlDeno6oaGhPs3WwWw288EHH7B3717Wrl1LVlYW8+fPZ+TIkZSVldGvXz+GDx/ul+nAFUVh7dq1XHPNNRw8eJDU1FTuv/9+evfuTWFhIVOmTGHQoEGEhYX5PJue2w3023atra04nU5+9Nj8qo0AAAeZSURBVKMfAZ55Qr766ivCwsK806knJCSQmJjoXRvFl1RVZdWqVfTr1887tmLbtm1MmzYNVVXZtWsXmZmZJCUl+Tyb1H3JHgwdamlpYdu2bWiaxu233866devYuXMn4eHhzJkzh9jYWEJCQigpKWH48OE+zdbc3MwHH3yAy+UiJSWFoUOHAp7TFYuLi/nxj39MWVkZ//rXv/iP//gPn2aD89vu5ptv5vDhw2RnZ3tXbDWbzTidTgoLC8nMzPRpto62U1WViRMnEhwczNChQ709VL169UJVVQ4ePOhdw8VX9NxuoO+2a21tJTc3l5qaGm9RkZWVxbBhw1i1ahW9e/f27tQTEhJ8mq2j3QBGjBiB2WxGVVVSUlK8Az5XrVpFWVmZd9C4JHUV2YOhQ8888wxhYWG0t7djt9txuVwkJCRwzz330NrayunTp/n444+ZNWsWwcHBPs323HPPkZCQQGxsLEeOHCE+Pp7Q0FD+8Y9/kJ2dze23306fPn3Izs72yyluHW1ns9lwu920tLR4x4homkZbWxsbN27kpz/9qV/aruO4/MmTJ9E0jfT0dFpbWzl48CBNTU18/PHH3HvvvT7Ppud2A3233VNPPUVYWBiqqtLQ0EBhYSFtbW1ce+21nD59mtdff51evXr5ZZnzjv+v0dHRVFRUEBERQUpKCgaDgUOHDuFwOPjiiy94+OGH5cBOqcvJHgydqa6uJjQ0lNmzZwOepcSLi4s5fvw4+fn57N69m8jISObOnevz0wNLSkoAuOuuuwDYuHEjn3zyCbfccgvZ2dncc889AH6ZkhkubLszZ85QXFxMfX09APn5+cTFxTF79myfT2vd0XazZs0CYNOmTeTl5TFy5EgaGxv58MMP6dWrF3PmzPH566rndgP9t11YWJj3b7/j/+vhw4dRFIVZs2YRERGB0ej7t9pv/n/dtGkTubm5jBw5EqPRiNPp5NVXX+WXv/ylXw7bSN2f7MHQGUVR2LhxI21tbfTv35+wsDASEhKw2+3s2bOHhx56iEn/f3t38wpdG8cB/DuHGUwT3UMY0yBKSiFvizFmZCGlLMQslJSdkiwlkrUFFv4CCxsWXppRkrcYjQV5C4WFybvRSBkyuRe6T49u8zxP4+QcM9/Pbo7T8ZtvJr+5rnOuq6JCtrnS1dVVcQQjLi4Os7OzaGpqQnFxMba3txEIBGTbuyBYdvf399je3kZbW5tisouNjYXT6URVVRUSExOh0WhQWloqy1LlSs8N+FnZGQwGvL6+Yn5+Hnl5eR+mmr7bZ7nZbDZoNBqo1Wrk5ubCZrPJUhuFPy4VrjBarRYtLS24vLyEw+GA1+tFbGwsLBYLtFotdnZ2ZKvt169faGhogF6vh0qlgtFohCAIeHl5wcbGBiYmJr59jvmfgmVntVqh0+mwv78vW22fZadWq8Ub7Obm5mT7B67k3ICfl11MTAzKy8uRkpKCo6MjWeoCgucWHR0Nt9sNh8OB6upq2eqj8McGQ4FycnJQVFSEi4sLOBwOLC0twefzYX9/X7ZvQsD7t7X8/HwkJycDeH+23mAwwOPxYGZmBna7XbbdPv8Ilt3e3p7isktJSYHH48H09LTs2Sk1N+DnZre7u6vYvzmlfF4pvHGpcAW7urrC5uYm1tbWkJSUhMzMTNTV1cld1gdDQ0NwuVxobGxEQ0OD3OWImF1ofkJuALMLlRJzo/DFBuOH8Pv9irzL++DgALOzs+js7JS7lKCYXWiUmhvA7EKl9NwovLDBoC97fn6W5dHFcMDsQsfsQsPc6LuwwSAiIiLJ8Q4fIiIikhwbDCIiIpIcGwwiIiKSHBsMoghzfX0Nu92Ovr6+v342MjICu92Oh4eHkK49Pj6OjY0N8VpTU1NfqpWIfi42GEQRSK1W4/z8HDc3N+Ixv9+Pw8PDL113d3cXgUDgq+URURjgZmdEEUgQBJjNZqysrKC+vh4A4Ha7UVJSgpmZGQDvm2M5nU4IgoCEhAS0trYiLS0NIyMjiIuLw9nZGW5vb5GRkYH29nYsLi7i+PgYo6Oj4gqRR0dH6Onpgc/ng8lkQkdHhyLXhyAi6XEEgyhC2Ww2rKysiK+XlpZQWVkJ4H0kYnJyEn19fRgYGIDFYsHAwAD+PNV+enqK7u5uDA4O4ubmBi6XCzU1NcjOzkZzczPKysoAAF6vF729vRgeHsbd3R3cbve3v08ikgcbDKIIlZWVBUEQcHJygtvbWzw9PSE9PR0AsLW1BbPZLG7PXllZCa/XK06pFBQUiBtnmUwmPD4+fvo7SktLERMTA0EQYDKZ4PP5vufNEZHsOEVCFMEqKiqwvLyM+Ph4WK1W8bhKpYJKpfrr/NfXVwCARqP5cG6w9fqioqL+13lEFH44gkEUwaxWK9bX1+FyuWCxWMTjhYWFWF1dFZ8mWVhYgE6nQ2pq6r9eLyoqSmxCiCiycQSDKILp9XoYjUZotVrodDrxeF5eHmpra9Hf34+3tzfEx8ejq6vrP7f3Li4uxtjYGJsMIuJeJERERCQ9TpEQERGR5NhgEBERkeTYYBAREZHk2GAQERGR5NhgEBERkeTYYBAREZHk2GAQERGR5NhgEBERkeR+A0pq+gHSFB2DAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(Maharashtra.Date,Maharashtra.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(Maharashtra.Date,Maharashtra.Deaths,label=\"Deaths\")\n",
    "plt.plot(Maharashtra.Date,Maharashtra.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of Maharastra 2020 \")\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(Maharashtra.Date[0:118:15].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(Maharashtra[\"Confirmed\"])\n",
    "deceased = sum(Maharashtra[\"Deaths\"])\n",
    "recovered = sum(Maharashtra[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of Maharashtra\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tamil Nadu analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 459,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "61      07/03/20\n",
       "703     06/04/20\n",
       "1665    06/05/20\n",
       "2695    05/06/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 459,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TamilNadu.Date[0:110:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(TamilNadu.Date,TamilNadu.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(TamilNadu.Date,TamilNadu.Deaths,label=\"Deaths\")\n",
    "plt.plot(TamilNadu.Date,TamilNadu.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of TamilNadu 2020 \")\n",
    "plt.xlabel(\"Months\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(TamilNadu.Date[0:110:15].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(TamilNadu[\"Confirmed\"])\n",
    "deceased = sum(TamilNadu[\"Deaths\"])\n",
    "recovered = sum(TamilNadu[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of TamilNadu\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Delhi analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34      02/03/20\n",
       "535     01/04/20\n",
       "1485    01/05/20\n",
       "2494    31/05/20\n",
       "3575    30/06/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 464,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Delhi.Date[0:125:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(Delhi.Date,Delhi.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(Delhi.Date,Delhi.Deaths,label=\"Deaths\")\n",
    "plt.plot(Delhi.Date,Delhi.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of Delhi 2020 \")\n",
    "plt.xlabel(\"Months\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(Delhi.Date[0:110:15].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(Delhi[\"Confirmed\"])\n",
    "deceased = sum(Delhi[\"Deaths\"])\n",
    "recovered = sum(Delhi[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of Delhi\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gujarat analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "231     20/03/20\n",
       "1100    19/04/20\n",
       "2077    19/05/20\n",
       "3145    18/06/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 470,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Gujarat.Date[0:107:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 477,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(Gujarat.Date,Gujarat.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(Gujarat.Date,Gujarat.Deaths,label=\"Deaths\")\n",
    "plt.plot(Gujarat.Date,Gujarat.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of Delhi 2020 \")\n",
    "plt.xlabel(\"Months\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(Gujarat.Date[0:107:30].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 478,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(Gujarat[\"Confirmed\"])\n",
    "deceased = sum(Gujarat[\"Deaths\"])\n",
    "recovered = sum(Gujarat[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of Gujarat\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## UttarPradesh analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 482,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "39      04/03/20\n",
       "615     03/04/20\n",
       "1572    03/05/20\n",
       "2591    02/06/20\n",
       "3672    02/07/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 482,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "UttarPradesh.Date[0:123:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 483,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(UttarPradesh.Date,UttarPradesh.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(UttarPradesh.Date,UttarPradesh.Deaths,label=\"Deaths\")\n",
    "plt.plot(UttarPradesh.Date,UttarPradesh.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of Delhi 2020 \")\n",
    "plt.xlabel(\"Months\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(UttarPradesh.Date[0:107:30].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(UttarPradesh[\"Confirmed\"])\n",
    "deceased = sum(UttarPradesh[\"Deaths\"])\n",
    "recovered = sum(UttarPradesh[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of Gujarat\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rajasthan analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 490,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36      03/03/20\n",
       "581     02/04/20\n",
       "1535    02/05/20\n",
       "2549    01/06/20\n",
       "3630    01/07/20\n",
       "Name: Date, dtype: object"
      ]
     },
     "execution_count": 490,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Rajasthan.Date[0:124:30]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "plt.plot(Rajasthan.Date,Rajasthan.Confirmed,label=\"Confirmed\")\n",
    "plt.plot(Rajasthan.Date,Rajasthan.Deaths,label=\"Deaths\")\n",
    "plt.plot(Rajasthan.Date,Rajasthan.Cured,label=\"Cured\")\n",
    "plt.title(\"Relation between Infected , Recovered & Deceased personal of Delhi 2020 \")\n",
    "plt.xlabel(\"Months\")\n",
    "plt.ylabel(\"No of cases cases\")\n",
    "plt.xticks(Rajasthan.Date[0:107:30].tolist(),rotation=55)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 492,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "infected = sum(Rajasthan[\"Confirmed\"])\n",
    "deceased = sum(Rajasthan[\"Deaths\"])\n",
    "recovered = sum(Rajasthan[\"Cured\"])\n",
    "\n",
    "labels = ['Infected', 'Recovered', 'Deceased']\n",
    "sizes = [infected, recovered, deceased]\n",
    "colors = ['lightcoral', 'yellowgreen', 'red']\n",
    "explode = (0, 0, 0) \n",
    "plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True)\n",
    "plt.title(\"Percentage distribution Of Covid-19 Infected, Recovered, Deceased from March till July 2020 of Gujarat\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Wasn't able to perform CMR & RR due to RuntimeWarning: invalid value encountered in long_scalars even after converting to ndarry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## B. Correlation heatmap for various parameters\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Mortality Rate'] = (data['Confirmed']/data['Deaths']).round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Recovery Rate'] = (data['Cured']/data['Confirmed']).round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb8c82f4710>"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(data.corr(),annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## C. Build a model for predicting the confirmed and recovered on any dates past 15th July 2020\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1 = pd.read_csv('state.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 357 entries, 0 to 356\n",
      "Data columns (total 41 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   Date    357 non-null    object\n",
      " 1   Status  357 non-null    object\n",
      " 2   TT      357 non-null    int64 \n",
      " 3   AN      357 non-null    int64 \n",
      " 4   AP      357 non-null    int64 \n",
      " 5   AR      357 non-null    int64 \n",
      " 6   AS      357 non-null    int64 \n",
      " 7   BR      357 non-null    int64 \n",
      " 8   CH      357 non-null    int64 \n",
      " 9   CT      357 non-null    int64 \n",
      " 10  DN      357 non-null    int64 \n",
      " 11  DD      357 non-null    int64 \n",
      " 12  DL      357 non-null    int64 \n",
      " 13  GA      357 non-null    int64 \n",
      " 14  GJ      357 non-null    int64 \n",
      " 15  HR      357 non-null    int64 \n",
      " 16  HP      357 non-null    int64 \n",
      " 17  JK      357 non-null    int64 \n",
      " 18  JH      357 non-null    int64 \n",
      " 19  KA      357 non-null    int64 \n",
      " 20  KL      357 non-null    int64 \n",
      " 21  LA      357 non-null    int64 \n",
      " 22  LD      357 non-null    int64 \n",
      " 23  MP      357 non-null    int64 \n",
      " 24  MH      357 non-null    int64 \n",
      " 25  MN      357 non-null    int64 \n",
      " 26  ML      357 non-null    int64 \n",
      " 27  MZ      357 non-null    int64 \n",
      " 28  NL      357 non-null    int64 \n",
      " 29  OR      357 non-null    int64 \n",
      " 30  PY      357 non-null    int64 \n",
      " 31  PB      357 non-null    int64 \n",
      " 32  RJ      357 non-null    int64 \n",
      " 33  SK      357 non-null    int64 \n",
      " 34  TN      357 non-null    int64 \n",
      " 35  TG      357 non-null    int64 \n",
      " 36  TR      357 non-null    int64 \n",
      " 37  UP      357 non-null    int64 \n",
      " 38  UT      357 non-null    int64 \n",
      " 39  WB      357 non-null    int64 \n",
      " 40  UN      357 non-null    int64 \n",
      "dtypes: int64(39), object(2)\n",
      "memory usage: 114.5+ KB\n"
     ]
    }
   ],
   "source": [
    "data1.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "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>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>TT</th>\n",
       "      <th>AN</th>\n",
       "      <th>AP</th>\n",
       "      <th>AR</th>\n",
       "      <th>AS</th>\n",
       "      <th>BR</th>\n",
       "      <th>CH</th>\n",
       "      <th>CT</th>\n",
       "      <th>...</th>\n",
       "      <th>PB</th>\n",
       "      <th>RJ</th>\n",
       "      <th>SK</th>\n",
       "      <th>TN</th>\n",
       "      <th>TG</th>\n",
       "      <th>TR</th>\n",
       "      <th>UP</th>\n",
       "      <th>UT</th>\n",
       "      <th>WB</th>\n",
       "      <th>UN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>Confirmed</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>Recovered</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>Deceased</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date     Status  TT  AN  AP  AR  AS  BR  CH  CT  ...  PB  RJ  SK  TN  \\\n",
       "0  14-Mar-20  Confirmed  81   0   1   0   0   0   0   0  ...   1   3   0   1   \n",
       "1  14-Mar-20  Recovered   9   0   0   0   0   0   0   0  ...   0   1   0   0   \n",
       "2  14-Mar-20   Deceased   2   0   0   0   0   0   0   0  ...   0   0   0   0   \n",
       "\n",
       "   TG  TR  UP  UT  WB  UN  \n",
       "0   1   0  12   0   0   0  \n",
       "1   0   0   4   0   0   0  \n",
       "2   0   0   0   0   0   0  \n",
       "\n",
       "[3 rows x 41 columns]"
      ]
     },
     "execution_count": 298,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Confirmed', 'Recovered', 'Deceased'], dtype=object)"
      ]
     },
     "execution_count": 299,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1['Status'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1['Status'] = data1['Status'].replace(\"Confirmed\", \"0\")\n",
    "data1['Status'] = data1['Status'].replace(\"Recovered\", \"1\")\n",
    "data1['Status'] = data1['Status'].replace(\"Deceased\", \"2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        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>Date</th>\n",
       "      <th>Status</th>\n",
       "      <th>TT</th>\n",
       "      <th>AN</th>\n",
       "      <th>AP</th>\n",
       "      <th>AR</th>\n",
       "      <th>AS</th>\n",
       "      <th>BR</th>\n",
       "      <th>CH</th>\n",
       "      <th>CT</th>\n",
       "      <th>...</th>\n",
       "      <th>PB</th>\n",
       "      <th>RJ</th>\n",
       "      <th>SK</th>\n",
       "      <th>TN</th>\n",
       "      <th>TG</th>\n",
       "      <th>TR</th>\n",
       "      <th>UP</th>\n",
       "      <th>UT</th>\n",
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       "      <th>UN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>0</td>\n",
       "      <td>81</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14-Mar-20</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date Status  TT  AN  AP  AR  AS  BR  CH  CT  ...  PB  RJ  SK  TN  TG  \\\n",
       "0  14-Mar-20      0  81   0   1   0   0   0   0   0  ...   1   3   0   1   1   \n",
       "1  14-Mar-20      1   9   0   0   0   0   0   0   0  ...   0   1   0   0   0   \n",
       "2  14-Mar-20      2   2   0   0   0   0   0   0   0  ...   0   0   0   0   0   \n",
       "\n",
       "   TR  UP  UT  WB  UN  \n",
       "0   0  12   0   0   0  \n",
       "1   0   4   0   0   0  \n",
       "2   0   0   0   0   0  \n",
       "\n",
       "[3 rows x 41 columns]"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1.drop(columns=['Date'],inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### separating Independent & dependent col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Status', 'TT', 'AN', 'AP', 'AR', 'AS', 'BR', 'CH', 'CT', 'DN', 'DD',\n",
       "       'DL', 'GA', 'GJ', 'HR', 'HP', 'JK', 'JH', 'KA', 'KL', 'LA', 'LD', 'MP',\n",
       "       'MH', 'MN', 'ML', 'MZ', 'NL', 'OR', 'PY', 'PB', 'RJ', 'SK', 'TN', 'TG',\n",
       "       'TR', 'UP', 'UT', 'WB', 'UN'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 303,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1.columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[81,  0,  1,  0,  0,  0,  0,  0,  0,  0,  7,  0,  0, 14,  0,  2,\n",
       "         0,  6, 19,  0,  0,  0, 14,  0,  0,  0,  0,  0,  0,  1,  3,  0,\n",
       "         1,  1,  0, 12,  0,  0,  0],\n",
       "       [ 9,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,\n",
       "         0,  0,  3,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,\n",
       "         0,  0,  0,  4,  0,  0,  0],\n",
       "       [ 2,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,\n",
       "         0,  1,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "         0,  0,  0,  0,  0,  0,  0],\n",
       "       [27,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,\n",
       "         0,  0,  5,  0,  0,  0, 18,  0,  0,  0,  0,  0,  0,  0,  1,  0,\n",
       "         0,  2,  0,  1,  0,  0,  0],\n",
       "       [ 4,  0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  0,  0,  0,  0,  0,\n",
       "         0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  0,  2,  0,\n",
       "         0,  1,  0,  0,  0,  0,  0]])"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = data1[['TT', 'AN', 'AP', 'AR', 'AS', 'BR', 'CH', 'CT', 'DN', 'DD',\n",
    "       'DL', 'GA', 'GJ', 'HR', 'HP', 'JK', 'JH', 'KA', 'KL', 'LA', 'LD', 'MP',\n",
    "       'MH', 'MN', 'ML', 'MZ', 'NL', 'OR', 'PY', 'PB', 'RJ', 'SK', 'TN', 'TG',\n",
    "       'TR', 'UP', 'UT', 'WB', 'UN']] .values  \n",
    "x[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['0', '1', '2', '0', '1'], dtype=object)"
      ]
     },
     "execution_count": 305,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = data1['Status'].values\n",
    "y[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 306,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "         0.        , -0.86965095, -0.64194987, -0.38689116, -0.15703169,\n",
       "        -0.21667963, -0.32872659, -0.51703245, -0.38309254, -0.46556148,\n",
       "        -0.78525174, -0.18133977, -0.56783721, -0.39150599, -0.40630124,\n",
       "        -0.64604643, -0.5071805 , -0.60619091, -0.05991803]])"
      ]
     },
     "execution_count": 306,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = preprocessing.StandardScaler().fit(x).transform(x.astype(float))\n",
    "x[0:5]  #standardization of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set: (285, 39) (285,)\n",
      "Test set: (72, 39) (72,)\n"
     ]
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split( x, y, test_size=0.2, random_state=2)\n",
    "print ('Train set:', x_train.shape,  y_train.shape)\n",
    "print ('Test set:', x_test.shape,  y_test.shape) #trainning model and predicting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 330,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=3, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 330,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k = 3\n",
    "neigh = KNeighborsClassifier(n_neighbors = k).fit(x_train,y_train)\n",
    "neigh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2', '2', '2', '2', '1'], dtype=object)"
      ]
     },
     "execution_count": 331,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat = neigh.predict(x_test)  \n",
    "yhat[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 337,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model accuracy is 0.69\n"
     ]
    }
   ],
   "source": [
    "score = neigh.score(x_test, y_test)\n",
    "print(\"Model accuracy is {}\".format(score.round(2))) #model accuracy score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## D. Build a classifier for severity gauging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3135 entries, 0 to 3134\n",
      "Data columns (total 12 columns):\n",
      " #   Column                    Non-Null Count  Dtype \n",
      "---  ------                    --------------  ----- \n",
      " 0   Date                      3135 non-null   object\n",
      " 1   Time                      3135 non-null   object\n",
      " 2   State/UnionTerritory      3135 non-null   object\n",
      " 3   ConfirmedIndianNational   3135 non-null   object\n",
      " 4   Gender                    3135 non-null   object\n",
      " 5   ConfirmedForeignNational  3135 non-null   object\n",
      " 6   Age                       3135 non-null   int64 \n",
      " 7   Serious symptoms          3135 non-null   object\n",
      " 8   Less common symptoms      3135 non-null   object\n",
      " 9   Most common symptoms      3135 non-null   object\n",
      " 10  Severity                  3135 non-null   object\n",
      " 11  Patient_Status            3135 non-null   object\n",
      "dtypes: int64(1), object(11)\n",
      "memory usage: 294.0+ KB\n"
     ]
    }
   ],
   "source": [
    "data2 = pd.read_csv('PAML_COVID_Dataset Sheet1.csv')\n",
    "data2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "metadata": {},
   "outputs": [],
   "source": [
    "data2.drop(columns=[\"Date\",\"Time\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['State/UnionTerritory', 'ConfirmedIndianNational', 'Gender ',\n",
       "       'ConfirmedForeignNational', 'Age ', 'Serious symptoms',\n",
       "       'Less common symptoms', 'Most common symptoms', 'Severity',\n",
       "       'Patient_Status '],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 394,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "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>State/UnionTerritory</th>\n",
       "      <th>ConfirmedIndianNational</th>\n",
       "      <th>Gender</th>\n",
       "      <th>ConfirmedForeignNational</th>\n",
       "      <th>Age</th>\n",
       "      <th>Serious symptoms</th>\n",
       "      <th>Less common symptoms</th>\n",
       "      <th>Most common symptoms</th>\n",
       "      <th>Severity</th>\n",
       "      <th>Patient_Status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Kerala</td>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>loss of speech or movement</td>\n",
       "      <td>a rash on skin, or discolouration of fingers o...</td>\n",
       "      <td>dry cough</td>\n",
       "      <td>Mild</td>\n",
       "      <td>flu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kerala</td>\n",
       "      <td>1</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>chest pain or pressure</td>\n",
       "      <td>loss of taste or smell</td>\n",
       "      <td>dry cough</td>\n",
       "      <td>Seviour</td>\n",
       "      <td>Covid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kerala</td>\n",
       "      <td>2</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>difficulty breathing or shortness of breath</td>\n",
       "      <td>conjunctivitis</td>\n",
       "      <td>tiredness</td>\n",
       "      <td>Seviour</td>\n",
       "      <td>Covid</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kerala</td>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>difficulty breathing or shortness of breath</td>\n",
       "      <td>diarrhoea</td>\n",
       "      <td>fever</td>\n",
       "      <td>Seviour</td>\n",
       "      <td>Covid</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  State/UnionTerritory ConfirmedIndianNational Gender   \\\n",
       "0               Kerala                       1   Male    \n",
       "1               Kerala                       1  Female   \n",
       "2               Kerala                       2   Male    \n",
       "3               Kerala                       3  Female   \n",
       "\n",
       "  ConfirmedForeignNational  Age                              Serious symptoms  \\\n",
       "0                        0    77                   loss of speech or movement   \n",
       "1                        0    23                       chest pain or pressure   \n",
       "2                        0    90  difficulty breathing or shortness of breath   \n",
       "3                        0    18  difficulty breathing or shortness of breath   \n",
       "\n",
       "                                Less common symptoms Most common symptoms  \\\n",
       "0  a rash on skin, or discolouration of fingers o...            dry cough   \n",
       "1                             loss of taste or smell            dry cough   \n",
       "2                                     conjunctivitis            tiredness   \n",
       "3                                          diarrhoea                fever   \n",
       "\n",
       "  Severity Patient_Status   \n",
       "0     Mild             flu  \n",
       "1  Seviour           Covid  \n",
       "2  Seviour           Covid  \n",
       "3  Seviour           Covid  "
      ]
     },
     "execution_count": 401,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data2.head(4) #Patient_Status col is the end vales need to patient "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "metadata": {},
   "outputs": [],
   "source": [
    "labelEncoder = LabelEncoder()\n",
    "x[:,0] = labelEncoder.fit_transform(x[:,0])\n",
    "x[:,2] = labelEncoder.fit_transform(x[:,2])\n",
    "x[:,5] = labelEncoder.fit_transform(x[:,5])\n",
    "x[:,6] = labelEncoder.fit_transform(x[:,6]) #converting string into numberic data to perform ML\n",
    "x[:,7] = labelEncoder.fit_transform(x[:,7])\n",
    "x[:,8] = labelEncoder.fit_transform(x[:,8])\n",
    "x[:,9] = labelEncoder.fit_transform(x[:,9])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>77</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>90</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3130</th>\n",
       "      <td>35</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3131</th>\n",
       "      <td>38</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>73</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3132</th>\n",
       "      <td>37</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>18</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3133</th>\n",
       "      <td>39</td>\n",
       "      <td>-</td>\n",
       "      <td>1</td>\n",
       "      <td>-</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3134</th>\n",
       "      <td>5</td>\n",
       "      <td>-</td>\n",
       "      <td>0</td>\n",
       "      <td>-</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3135 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       0  1  2  3   4  5  6  7  8  9\n",
       "0     19  1  1  0  77  2  0  0  0  1\n",
       "1     19  1  0  0  23  0  5  0  2  0\n",
       "2     19  2  1  0  90  1  2  2  2  0\n",
       "3     19  3  0  0  18  1  3  1  2  0\n",
       "4     19  3  1  0  24  0  3  2  2  0\n",
       "...   .. .. .. ..  .. .. .. .. .. ..\n",
       "3130  35  -  1  -  66  0  4  1  1  0\n",
       "3131  38  -  1  -  73  2  5  0  0  0\n",
       "3132  37  -  1  -  18  2  2  0  2  0\n",
       "3133  39  -  1  -  79  0  4  1  2  0\n",
       "3134   5  -  0  -  11  0  5  2  1  1\n",
       "\n",
       "[3135 rows x 10 columns]"
      ]
     },
     "execution_count": 400,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x1 = pd.DataFrame(x)\n",
    "x1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "metadata": {},
   "outputs": [],
   "source": [
    "x1[1] = x1[1].replace('-',0)\n",
    "x1[3] = x1[3].replace('-',0) #replacing - with 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### separating Independent & dependent col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[19, '1', 1, '0', 77, 2, 0, 0, 0],\n",
       "       [19, '1', 0, '0', 23, 0, 5, 0, 2],\n",
       "       [19, '2', 1, '0', 90, 1, 2, 2, 2],\n",
       "       [19, '3', 0, '0', 18, 1, 3, 1, 2],\n",
       "       [19, '3', 1, '0', 24, 0, 3, 2, 2]], dtype=object)"
      ]
     },
     "execution_count": 408,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = x1[[0,1,2,3,4,5,6,7,8]] .values  \n",
    "x[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 416,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = x1[9].values\n",
    "y=y.astype('int') #converting object into int for calculation\n",
    "y[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.05521939, -0.07996629,  0.9971333 , -0.14722546,  0.89554084,\n",
       "         1.24173161, -1.5043959 , -1.20859338, -1.24718755],\n",
       "       [-0.05521939, -0.07996629, -1.00287495, -0.14722546, -1.05297353,\n",
       "        -1.22442525,  0.96253639, -1.20859338,  1.22980514],\n",
       "       [-0.05521939,  0.02898387,  0.9971333 , -0.14722546,  1.36462764,\n",
       "         0.00865318, -0.51762299,  1.24062462,  1.22980514],\n",
       "       [-0.05521939,  0.13793403, -1.00287495, -0.14722546, -1.23339153,\n",
       "         0.00865318, -0.02423653,  0.01601562,  1.22980514],\n",
       "       [-0.05521939,  0.13793403,  0.9971333 , -0.14722546, -1.01688993,\n",
       "        -1.22442525, -0.02423653,  1.24062462,  1.22980514]])"
      ]
     },
     "execution_count": 423,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = preprocessing.StandardScaler().fit(x).transform(x.astype(float))\n",
    "x[0:5] #Standardization of data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set: (2508, 9) (2508,)\n",
      "Test set: (627, 9) (627,)\n"
     ]
    }
   ],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split( x, y, test_size=0.2, random_state=2)\n",
    "print ('Train set:', x_train.shape,  y_train.shape)\n",
    "print ('Test set:', x_test.shape,  y_test.shape)  #splitting data into train & test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=1, p=2,\n",
       "                     weights='uniform')"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier(n_neighbors=1)\n",
    "knn.fit(x_train,y_train)  #trainning model and predicting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 0, 1])"
      ]
     },
     "execution_count": 431,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yhat = knn.predict(x_test)\n",
    "yhat[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set Accuracy:  0.9996012759170654\n",
      "Test set Accuracy:  0.48165869218500795\n"
     ]
    }
   ],
   "source": [
    "print(\"Train set Accuracy: \", metrics.accuracy_score(y_train, knn.predict(x_train)))\n",
    "print(\"Test set Accuracy: \", metrics.accuracy_score(y_test, yhat)) #accuracy score for test data & train data "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dataset sources: https://www.covid19india.org & http://kaggle.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## By Vigneshwaram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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