naeem ullah.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "kkf\n"
     ]
    }
   ],
   "source": [
    "print(\"kkf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%pip install numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: python--docx in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (1.1.2)\n",
      "Requirement already satisfied: lxml>=3.1.0 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from python--docx) (5.3.0)\n",
      "Requirement already satisfied: typing-extensions>=4.9.0 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from python--docx) (4.12.2)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install python--docx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from docx import Document"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "document=Document(\"sample.docx\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<docx.document.Document object at 0x00000236880A9400>\n"
     ]
    }
   ],
   "source": [
    "print(document)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'My name is ali'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "document.paragraphs[1].text"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%pip install PyPDF2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PyPDF2 import PdfReader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "reader=PdfReader('dummy.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "txt=reader.pages[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Dumm y PDF file'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "txt.extract_text()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "naeem=open('sample4.json','r')\n",
    "data=naeem.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "ename": "JSONDecodeError",
     "evalue": "Expecting value: line 1 column 1 (char 0)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[17], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m fnaeem\u001b[38;5;241m=\u001b[39m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\\Lib\\json\\__init__.py:346\u001b[0m, in \u001b[0;36mloads\u001b[1;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[0;32m    341\u001b[0m     s \u001b[38;5;241m=\u001b[39m s\u001b[38;5;241m.\u001b[39mdecode(detect_encoding(s), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msurrogatepass\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m    343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[0;32m    344\u001b[0m         parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[0;32m    345\u001b[0m         parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[1;32m--> 346\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m    348\u001b[0m     \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONDecoder\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\\Lib\\json\\decoder.py:345\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[1;34m(self, s, _w)\u001b[0m\n\u001b[0;32m    340\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecode\u001b[39m(\u001b[38;5;28mself\u001b[39m, s, _w\u001b[38;5;241m=\u001b[39mWHITESPACE\u001b[38;5;241m.\u001b[39mmatch):\n\u001b[0;32m    341\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[0;32m    342\u001b[0m \u001b[38;5;124;03m    containing a JSON document).\u001b[39;00m\n\u001b[0;32m    343\u001b[0m \n\u001b[0;32m    344\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m--> 345\u001b[0m     obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    346\u001b[0m     end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n\u001b[0;32m    347\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m end \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(s):\n",
      "File \u001b[1;32mC:\\Program Files\\WindowsApps\\PythonSoftwareFoundation.Python.3.13_3.13.496.0_x64__qbz5n2kfra8p0\\Lib\\json\\decoder.py:363\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[1;34m(self, s, idx)\u001b[0m\n\u001b[0;32m    361\u001b[0m     obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mscan_once(s, idx)\n\u001b[0;32m    362\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[1;32m--> 363\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpecting value\u001b[39m\u001b[38;5;124m\"\u001b[39m, s, err\u001b[38;5;241m.\u001b[39mvalue) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    364\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n",
      "\u001b[1;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)"
     ]
    }
   ],
   "source": [
    "fnaeem=json.loads(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'fnaeem' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[18], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mfnaeem\u001b[49m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'fnaeem' is not defined"
     ]
    }
   ],
   "source": [
    "fnaeem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'fnaeem' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[19], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m j \u001b[38;5;129;01min\u001b[39;00m \u001b[43mfnaeem\u001b[49m:\n\u001b[0;32m      2\u001b[0m     \u001b[38;5;28mprint\u001b[39m(j[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mage\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n",
      "\u001b[1;31mNameError\u001b[0m: name 'fnaeem' is not defined"
     ]
    }
   ],
   "source": [
    "for j in fnaeem:\n",
    "    print(j[\"age\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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>Age</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>16.00000</td>\n",
       "      <td>1.500000e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>48.68750</td>\n",
       "      <td>1.725333e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>35.55975</td>\n",
       "      <td>3.713435e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>20.00000</td>\n",
       "      <td>2.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27.50000</td>\n",
       "      <td>3.500000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>30.00000</td>\n",
       "      <td>7.000000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>61.75000</td>\n",
       "      <td>1.150000e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>156.00000</td>\n",
       "      <td>1.500000e+06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Age        Salary\n",
       "count   16.00000  1.500000e+01\n",
       "mean    48.68750  1.725333e+05\n",
       "std     35.55975  3.713435e+05\n",
       "min     20.00000  2.000000e+03\n",
       "25%     27.50000  3.500000e+04\n",
       "50%     30.00000  7.000000e+04\n",
       "75%     61.75000  1.150000e+05\n",
       "max    156.00000  1.500000e+06"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Name</th>\n",
       "      <th>Designation</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Salary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mukhtar</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Azziz</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mohsin</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Naveed Fatima</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>30.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Babar</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Aqsa</td>\n",
       "      <td>Scientist</td>\n",
       "      <td>F</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Rafia</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>29.0</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Samra</td>\n",
       "      <td>Scientist</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Eman</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>F</td>\n",
       "      <td>28.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Abdullah</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Mosib</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>60.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ahmad</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ahsan</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>156.0</td>\n",
       "      <td>110000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Naseem</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>80.0</td>\n",
       "      <td>16000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Qaiser</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>170000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>85.0</td>\n",
       "      <td>190000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name Designation Gender    Age     Salary\n",
       "0         Mukhtar   Professor      M   37.0   115000.0\n",
       "1           Azziz     Teacher      M   30.0    35000.0\n",
       "2          Mohsin    Engineer      M   29.0    50000.0\n",
       "3   Naveed Fatima     Analyst      F   30.0    70000.0\n",
       "4           Babar    Engineer      M   25.0  1500000.0\n",
       "5            Aqsa   Scientist      F   22.0        NaN\n",
       "6           Rafia     Analyst      F   29.0    20000.0\n",
       "7           Samra   Scientist      F   26.0   115000.0\n",
       "8            Eman    Engineer      F   28.0    35000.0\n",
       "9        Abdullah     Teacher      M   55.0        NaN\n",
       "10          Mosib   Professor      M   60.0    70000.0\n",
       "11          Ahmad    Engineer      M    NaN    90000.0\n",
       "12          Ahsan     trainer      M  156.0   110000.0\n",
       "13          Wajid     Teacher      M   67.0     2000.0\n",
       "14         Naseem     trainer      M   80.0    16000.0\n",
       "15         Qaiser   Professor      M   20.0   170000.0\n",
       "16          Wajid    Engineer      M   85.0   190000.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(17, 5)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     Professor\n",
       "1       Teacher\n",
       "2      Engineer\n",
       "3       Analyst\n",
       "4      Engineer\n",
       "5     Scientist\n",
       "6       Analyst\n",
       "7     Scientist\n",
       "8      Engineer\n",
       "9       Teacher\n",
       "10    Professor\n",
       "11     Engineer\n",
       "12      trainer\n",
       "13      Teacher\n",
       "14      trainer\n",
       "15    Professor\n",
       "16     Engineer\n",
       "Name: Designation, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Designation']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name           0\n",
       "Designation    0\n",
       "Gender         0\n",
       "Age            1\n",
       "Salary         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(1)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "dates = pd.date_range(\"20130101\", periods=6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatetimeIndex(['2013-01-01', '2013-01-02', '2013-01-03', '2013-01-04',\n",
       "               '2013-01-05', '2013-01-06'],\n",
       "              dtype='datetime64[ns]', freq='D')"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(np.random.randn(6, 5), index=dates, columns=['A', 'B', 'C', 'D', 'M'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
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       "      <th>D</th>\n",
       "      <th>M</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>-0.398408</td>\n",
       "      <td>-0.075111</td>\n",
       "      <td>-0.628705</td>\n",
       "      <td>-0.656808</td>\n",
       "      <td>1.827681</td>\n",
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       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>0.253255</td>\n",
       "      <td>-0.365007</td>\n",
       "      <td>-0.569741</td>\n",
       "      <td>-0.247165</td>\n",
       "      <td>0.651718</td>\n",
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       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>0.722499</td>\n",
       "      <td>1.810270</td>\n",
       "      <td>0.546160</td>\n",
       "      <td>-0.244187</td>\n",
       "      <td>0.733782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.407728</td>\n",
       "      <td>0.930295</td>\n",
       "      <td>-0.181744</td>\n",
       "      <td>0.641924</td>\n",
       "      <td>0.753338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.576611</td>\n",
       "      <td>-1.829873</td>\n",
       "      <td>1.356382</td>\n",
       "      <td>0.539133</td>\n",
       "      <td>1.079457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.113477</td>\n",
       "      <td>-0.291128</td>\n",
       "      <td>-1.290113</td>\n",
       "      <td>-0.308581</td>\n",
       "      <td>0.601771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D         M\n",
       "2013-01-01 -0.398408 -0.075111 -0.628705 -0.656808  1.827681\n",
       "2013-01-02  0.253255 -0.365007 -0.569741 -0.247165  0.651718\n",
       "2013-01-03  0.722499  1.810270  0.546160 -0.244187  0.733782\n",
       "2013-01-04 -0.407728  0.930295 -0.181744  0.641924  0.753338\n",
       "2013-01-05  0.576611 -1.829873  1.356382  0.539133  1.079457\n",
       "2013-01-06  0.113477 -0.291128 -1.290113 -0.308581  0.601771"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame(\n",
    "    {\n",
    "        \"A\": 1.0,\n",
    "        \"B\": pd.Timestamp(\"20130102\"),\n",
    "        \"C\": pd.Series(1, index=list(range(5)), dtype=\"float32\"),\n",
    "        \"D\": np.array([3] * 5, dtype=\"int32\"),\n",
    "        \"E\": pd.Categorical([\"test\", \"train\", \"test\", \"train\",\"NAN\"]),\n",
    "        \"F\": \"foo\"\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>train</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>test</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>train</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>NAN</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A          B    C  D      E    F\n",
       "0  1.0 2013-01-02  1.0  3   test  foo\n",
       "1  1.0 2013-01-02  1.0  3  train  foo\n",
       "2  1.0 2013-01-02  1.0  3   test  foo\n",
       "3  1.0 2013-01-02  1.0  3  train  foo\n",
       "4  1.0 2013-01-02  1.0  3    NAN  foo"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.143284\n",
       "B    0.029908\n",
       "C   -0.127960\n",
       "D   -0.045947\n",
       "M    0.941291\n",
       "dtype: float64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
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       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
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       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>0.722499</td>\n",
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       "      <td>-0.244187</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.407728</td>\n",
       "      <td>0.930295</td>\n",
       "      <td>-0.181744</td>\n",
       "      <td>0.641924</td>\n",
       "      <td>0.753338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>0.576611</td>\n",
       "      <td>-1.829873</td>\n",
       "      <td>1.356382</td>\n",
       "      <td>0.539133</td>\n",
       "      <td>1.079457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>0.113477</td>\n",
       "      <td>-0.291128</td>\n",
       "      <td>-1.290113</td>\n",
       "      <td>-0.308581</td>\n",
       "      <td>0.601771</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D         M\n",
       "2013-01-01 -0.398408 -0.075111 -0.628705 -0.656808  1.827681\n",
       "2013-01-02  0.253255 -0.365007 -0.569741 -0.247165  0.651718\n",
       "2013-01-03  0.722499  1.810270  0.546160 -0.244187  0.733782\n",
       "2013-01-04 -0.407728  0.930295 -0.181744  0.641924  0.753338\n",
       "2013-01-05  0.576611 -1.829873  1.356382  0.539133  1.079457\n",
       "2013-01-06  0.113477 -0.291128 -1.290113 -0.308581  0.601771"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.DataFrame({\n",
    "    \"name\":pd.Categorical([\"naeem\",\"hgf\"]),\n",
    "    \"age\":pd.Categorical([\"25\",\"30\"])\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
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       "      <th>age</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>naeem</td>\n",
       "      <td>25</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>hgf</td>\n",
       "      <td>30</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    name age\n",
       "0  naeem  25\n",
       "1    hgf  30"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = pd.Series(np.random.randint(0, 7, size=19))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0\n",
       "1     0\n",
       "2     5\n",
       "3     1\n",
       "4     2\n",
       "5     0\n",
       "6     1\n",
       "7     1\n",
       "8     5\n",
       "9     1\n",
       "10    0\n",
       "11    2\n",
       "12    5\n",
       "13    3\n",
       "14    3\n",
       "15    1\n",
       "16    5\n",
       "17    4\n",
       "18    2\n",
       "dtype: int32"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    5\n",
       "0    4\n",
       "5    4\n",
       "2    3\n",
       "3    2\n",
       "4    1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Name           0\n",
       "Designation    0\n",
       "Gender         0\n",
       "Age            1\n",
       "Salary         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mukhtar</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>37.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Azziz</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mohsin</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Naveed Fatima</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>30.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Babar</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Aqsa</td>\n",
       "      <td>Scientist</td>\n",
       "      <td>F</td>\n",
       "      <td>22.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Rafia</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>29.0</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Samra</td>\n",
       "      <td>Scientist</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Eman</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>F</td>\n",
       "      <td>28.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Abdullah</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>55.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Mosib</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>60.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ahmad</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ahsan</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>156.0</td>\n",
       "      <td>110000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Naseem</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>80.0</td>\n",
       "      <td>16000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Qaiser</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>170000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>85.0</td>\n",
       "      <td>190000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name Designation Gender    Age     Salary\n",
       "0         Mukhtar   Professor      M   37.0   115000.0\n",
       "1           Azziz     Teacher      M   30.0    35000.0\n",
       "2          Mohsin    Engineer      M   29.0    50000.0\n",
       "3   Naveed Fatima     Analyst      F   30.0    70000.0\n",
       "4           Babar    Engineer      M   25.0  1500000.0\n",
       "5            Aqsa   Scientist      F   22.0        NaN\n",
       "6           Rafia     Analyst      F   29.0    20000.0\n",
       "7           Samra   Scientist      F   26.0   115000.0\n",
       "8            Eman    Engineer      F   28.0    35000.0\n",
       "9        Abdullah     Teacher      M   55.0        NaN\n",
       "10          Mosib   Professor      M   60.0    70000.0\n",
       "11          Ahmad    Engineer      M    NaN    90000.0\n",
       "12          Ahsan     trainer      M  156.0   110000.0\n",
       "13          Wajid     Teacher      M   67.0     2000.0\n",
       "14         Naseem     trainer      M   80.0    16000.0\n",
       "15         Qaiser   Professor      M   20.0   170000.0\n",
       "16          Wajid    Engineer      M   85.0   190000.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.dropna(subset=['Salary'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Mukhtar</td>\n",
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       "      <td>37.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Azziz</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>30.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Mohsin</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>29.0</td>\n",
       "      <td>50000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Naveed Fatima</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>30.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Babar</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1500000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Rafia</td>\n",
       "      <td>Analyst</td>\n",
       "      <td>F</td>\n",
       "      <td>29.0</td>\n",
       "      <td>20000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Samra</td>\n",
       "      <td>Scientist</td>\n",
       "      <td>F</td>\n",
       "      <td>26.0</td>\n",
       "      <td>115000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Eman</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>F</td>\n",
       "      <td>28.0</td>\n",
       "      <td>35000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Mosib</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>60.0</td>\n",
       "      <td>70000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ahmad</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>90000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ahsan</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>156.0</td>\n",
       "      <td>110000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>M</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Naseem</td>\n",
       "      <td>trainer</td>\n",
       "      <td>M</td>\n",
       "      <td>80.0</td>\n",
       "      <td>16000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Qaiser</td>\n",
       "      <td>Professor</td>\n",
       "      <td>M</td>\n",
       "      <td>20.0</td>\n",
       "      <td>170000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Wajid</td>\n",
       "      <td>Engineer</td>\n",
       "      <td>M</td>\n",
       "      <td>85.0</td>\n",
       "      <td>190000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name Designation Gender    Age     Salary\n",
       "0         Mukhtar   Professor      M   37.0   115000.0\n",
       "1           Azziz     Teacher      M   30.0    35000.0\n",
       "2          Mohsin    Engineer      M   29.0    50000.0\n",
       "3   Naveed Fatima     Analyst      F   30.0    70000.0\n",
       "4           Babar    Engineer      M   25.0  1500000.0\n",
       "6           Rafia     Analyst      F   29.0    20000.0\n",
       "7           Samra   Scientist      F   26.0   115000.0\n",
       "8            Eman    Engineer      F   28.0    35000.0\n",
       "10          Mosib   Professor      M   60.0    70000.0\n",
       "11          Ahmad    Engineer      M    NaN    90000.0\n",
       "12          Ahsan     trainer      M  156.0   110000.0\n",
       "13          Wajid     Teacher      M   67.0     2000.0\n",
       "14         Naseem     trainer      M   80.0    16000.0\n",
       "15         Qaiser   Professor      M   20.0   170000.0\n",
       "16          Wajid    Engineer      M   85.0   190000.0"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: matplotlib in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (3.10.0)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (1.3.1)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (4.55.3)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (1.4.7)\n",
      "Requirement already satisfied: numpy>=1.23 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (2.2.0)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (11.0.0)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (3.2.0)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\naeem ullah joya\\appdata\\local\\packages\\pythonsoftwarefoundation.python.3.13_qbz5n2kfra8p0\\localcache\\local-packages\\python313\\site-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpoints=np.array([0,6])\n",
    "ypoints=np.array([0,250])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,ypoints)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xpoints=np.array([1,10])\n",
    "ypoints=np.array([1,100])\n",
    "plt.plot(xpoints, ypoints,marker='o')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "xpoints=np.array([2,4,8,3,5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e56c050>]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='v')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e5afc50>]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='h')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e443890>]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e4e3890>]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='<')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e66b4d0>]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2368e6fb110>]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(xpoints,marker='<')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "#%pip install Xlrd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic=pd.read_csv('titanic.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of      PassengerId  Survived  Pclass  \\\n",
       "0              1         0       3   \n",
       "1              2         1       1   \n",
       "2              3         1       3   \n",
       "3              4         1       1   \n",
       "4              5         0       3   \n",
       "..           ...       ...     ...   \n",
       "886          887         0       2   \n",
       "887          888         1       1   \n",
       "888          889         0       3   \n",
       "889          890         1       1   \n",
       "890          891         0       3   \n",
       "\n",
       "                                                  Name     Sex   Age  SibSp  \\\n",
       "0                              Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1    Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                               Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3         Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                             Allen, Mr. William Henry    male  35.0      0   \n",
       "..                                                 ...     ...   ...    ...   \n",
       "886                              Montvila, Rev. Juozas    male  27.0      0   \n",
       "887                       Graham, Miss. Margaret Edith  female  19.0      0   \n",
       "888           Johnston, Miss. Catherine Helen \"Carrie\"  female   NaN      1   \n",
       "889                              Behr, Mr. Karl Howell    male  26.0      0   \n",
       "890                                Dooley, Mr. Patrick    male  32.0      0   \n",
       "\n",
       "     Parch            Ticket     Fare Cabin Embarked  \n",
       "0        0         A/5 21171   7.2500   NaN        S  \n",
       "1        0          PC 17599  71.2833   C85        C  \n",
       "2        0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3        0            113803  53.1000  C123        S  \n",
       "4        0            373450   8.0500   NaN        S  \n",
       "..     ...               ...      ...   ...      ...  \n",
       "886      0            211536  13.0000   NaN        S  \n",
       "887      0            112053  30.0000   B42        S  \n",
       "888      2        W./C. 6607  23.4500   NaN        S  \n",
       "889      0            111369  30.0000  C148        C  \n",
       "890      0            370376   7.7500   NaN        Q  \n",
       "\n",
       "[891 rows x 12 columns]>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.describe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>887</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>Montvila, Rev. Juozas</td>\n",
       "      <td>male</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>211536</td>\n",
       "      <td>13.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>888</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Graham, Miss. Margaret Edith</td>\n",
       "      <td>female</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>112053</td>\n",
       "      <td>30.00</td>\n",
       "      <td>B42</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>888</th>\n",
       "      <td>889</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Johnston, Miss. Catherine Helen \"Carrie\"</td>\n",
       "      <td>female</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>W./C. 6607</td>\n",
       "      <td>23.45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>889</th>\n",
       "      <td>890</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Behr, Mr. Karl Howell</td>\n",
       "      <td>male</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>111369</td>\n",
       "      <td>30.00</td>\n",
       "      <td>C148</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
       "      <td>891</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Dooley, Mr. Patrick</td>\n",
       "      <td>male</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>370376</td>\n",
       "      <td>7.75</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     PassengerId  Survived  Pclass                                      Name  \\\n",
       "886          887         0       2                     Montvila, Rev. Juozas   \n",
       "887          888         1       1              Graham, Miss. Margaret Edith   \n",
       "888          889         0       3  Johnston, Miss. Catherine Helen \"Carrie\"   \n",
       "889          890         1       1                     Behr, Mr. Karl Howell   \n",
       "890          891         0       3                       Dooley, Mr. Patrick   \n",
       "\n",
       "        Sex   Age  SibSp  Parch      Ticket   Fare Cabin Embarked  \n",
       "886    male  27.0      0      0      211536  13.00   NaN        S  \n",
       "887  female  19.0      0      0      112053  30.00   B42        S  \n",
       "888  female   NaN      1      2  W./C. 6607  23.45   NaN        S  \n",
       "889    male  26.0      0      0      111369  30.00  C148        C  \n",
       "890    male  32.0      0      0      370376   7.75   NaN        Q  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PassengerId      0\n",
       "Survived         0\n",
       "Pclass           0\n",
       "Name             0\n",
       "Sex              0\n",
       "Age            177\n",
       "SibSp            0\n",
       "Parch            0\n",
       "Ticket           0\n",
       "Fare             0\n",
       "Cabin          687\n",
       "Embarked         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=titanic['Age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "y=titanic['Fare']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      22.0\n",
      "1      38.0\n",
      "2      26.0\n",
      "3      35.0\n",
      "4      35.0\n",
      "       ... \n",
      "886    27.0\n",
      "887    19.0\n",
      "888     NaN\n",
      "889    26.0\n",
      "890    32.0\n",
      "Name: Age, Length: 891, dtype: float64 0       7.2500\n",
      "1      71.2833\n",
      "2       7.9250\n",
      "3      53.1000\n",
      "4       8.0500\n",
      "        ...   \n",
      "886    13.0000\n",
      "887    30.0000\n",
      "888    23.4500\n",
      "889    30.0000\n",
      "890     7.7500\n",
      "Name: Fare, Length: 891, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2368b9fd6a0>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y, c='red', label='Age',alpha=1)\n",
    "plt.scatter(x, y, c='green', label='Fare',alpha=0.2)\n",
    "plt.title('titanic graph')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Fare')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# titanic['Age'].fillna(titanic['Age'].mean(),inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.int64(177)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic['Age'].isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y,edgecolors='red',facecolor='green')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Fare')\n",
    "plt.title('Age vs Fare')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2368eab6ad0>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color=['red' if age>30 else 'green' for age in x]\n",
    "plt.scatter(x,y,c=color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "expected 'else' after 'if' expression (3141848585.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  Cell \u001b[1;32mIn[88], line 1\u001b[1;36m\u001b[0m\n\u001b[1;33m    color=['red' if age>100 'yellow' elif age>50 else 'green' for age in x]\u001b[0m\n\u001b[1;37m           ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m expected 'else' after 'if' expression\n"
     ]
    }
   ],
   "source": [
    "color=['red' if age>100 'yellow' elif age>50 else 'green' for age in x]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2368eb41f90>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nD1u3bmX48OEMHDiQQ4cO3Yy6Wb366qvEx8dbf86cOXNTzyeEEEKIomVw9QHe3t7UqFEDgKZNm7J9+3a+/vprHnnkETIyMrh27VqOVpTY2FgiIiIAiIiIYNu2bTnKs8zysRyTFx8fH3x8fFytqhBCCCGKqQLnQTGbzaSnp9O0aVO8vLxYuXKldd/Ro0eJjo4mKioKgKioKPbv38/FixetxyxfvpygoCAiIyMLWhUhhBBC3CJcakF59dVX6dq1K5UqVSIxMZEZM2awZs0a/vnnH4KDgxk8eDCjR48mNDSUoKAgnn32WaKiomjZsiUAnTp1IjIykgEDBvDpp58SExPDG2+8wYgRI6SFRAghhBBWLgUoFy9e5PHHH+fChQsEBwfToEED/vnnH+69914Axo0bh06no3fv3qSnp9O5c2d++OEH6+P1ej1///03w4cPJyoqioCAAAYOHMh7773n3qsSQgghRLFW4DwoRUHyoAghhBDFT6HkQRFCCCGEuFkkQBFCCCGEx5EARQghhBAeRwIUIYQQQngcCVCEEEII4XEkQBFCCCGEx5EARQghhBAeRwIUIYQQQngcCVCEEEII4XEkQBFCCCGEx5EARQghhBAeRwIUIYQQQngcl1YzFqKwXEi8wN/H/iY5M5nI8Eg6VuvIrgu7+H7b96yLXodBZ6BbjW6MuHMENUJrOF2GTskdk2eaMplzaA4Td03k36v/UjqgNAMbDqTbHd2Ytm8asw/NJikjiQZlGvBMs2foVL0TiqLc7KdACGG1DfgO2Ah4AT2AZ4BqRVkpcZPJasbCo2SYMnhuyXNM2jUJs2pGURTMqpmSviW5mnYVg86A0WwEQK/o0Sk6/nz4T+6rdZ/DMioHV2bag9NoU6mN9djUzFS6z+jO6v9Wo1N02vEoqKjWYMasmq3nM6kmhjUdxoTuEyRIEaJQfAqMQfs+bby+TX/973lA1yKql8gPWc1YFFtPLniSibsmYlJNqKjW4OBq2lUAa3ACYFJNGM1G+vzRh7MJZ63bBy0YlGcZZxLOcO9v97I3Zq/12FdWvMLa02uBrEBERbX+bdlmOR/ATzt/YuKuiW6/diHEjVaiBSeQFZwAmIAM4EEgtrArJQqJBCjCYxy8eJDp+6fnCAocUVExmU1M3KkFDAcuHmDG/hl5lmFWzWSaMvlg3QcAJKQn8NOun1w6H4CCwuebPqcYNj4KUcyMQ2styYuKFqRMKrzqiEIlAYrwGDP2z8Cgc31YlEk1sfq/1U6VYVJNzDsyj5TMFHZf2E2aMc3l86moHL9ynLjUOJcfK4RwxVq01hJbzMCawqmKKHQSoAiPEZcah0LBxnXEpTguw6SaSEhPKNB5hBBC3FwSoAiPUTm4ssvdLQA6RUeHqh0AqBJSxWEZfgY/SvqWpEnZJvgZ/Fw+n4JCrbBahPmFufxYIYQr2mO7iwe0W1j7QqqLKGwSoAiP8XjDx60DVJ2loOCl82JY02FOlaFX9AxsOBAfgw+BPoEMazosz6nH9qiovBj1osziEeKmewHbXTwK4AMMKbzqiEIlAYrwGOWDyvPe3e/luc8SROiVrG9TekWPl96LPx/+k3KB5axlvHv3u3mWoVf0lA4ozZvt3rRuG3vPWNpXaZ+jbEsXkU7R5QheLGNbnm72NEOayIeiEDdfe+Dz6/+ffWyZHi04mQeULuxKiUIieVCER1FVlYm7JvLe2vc4l3gO0AKFnrV6MrTJUP48/CfrT6/XErXd0Y1nmj9DtZLVnC7j6y5fUym4Uo7jjWYjcw/P5aedP3Hq6iktUVujgXSp0YXf9//OrIOzshK1NX+Ge6reI60nQhSqHcD3aInaDMB9wHCgShHWSeSHK/dvCVCERzKZTeyO2U1SRhK1wmpRNrBsoZeRYcpg/pH5zDsyj6T0JOqWrsvQJkOpHlrd5boIseP8Dn7Z/QvR8dGUDihN/wb9aV+lvQS74rYiAYoQBXQ24Swdf+3I0bij1gyyekWPWTXz2b2f8WKrF4u6iqKYMJlNDP1rKJP3TLZmQrb87litI/MfmU+Ad0BRV1OIQiGZZIUoALNqpuv0rpy8ehLIyiBryUz70vKXmH9kfhHWUBQnH6z7gCl7pgBZmZAtv1edWsXTi54uqqoJ4dEkQBHiBstPLufAxQM50upnp1N0fLzh40KulSiOUjNTGbdlnM2ZZWbVzIz9MziXcK6QayaE55MARYgbLD6+2G42WrNqZuu5rVxNvVqItRLF0bZz24hPj7d7jFk188/JfwqpRkIUHxKgCHGDDFOGUxltM0wZhVAbUZylm9IdHqOgkG50fJwQtxsJUIS4QZOyTcg0Z9o9pmyJsoQHhBdSjURx1aBMgxy5e/KiotKsXLNCqpEQxYcEKELc4LH6jxHoHYjOxj8PnaLj2TufdTkDrbj9RJSIoHed3hiUvLsM9YqeRhGNJEARIg/yCSvEDUp4l+CPh/7AoDfkGIuiXP+vQ9UOMs1YOO3bbt9SpWSVXAGtXtET4hvC771/l1woQuRBAhQh8tC5Rmd2DN1B3/p98ffyR6foqBVWi2+7fsuivovw1nsXdRVFMVE6oDTbhmzj7XZvUy6wHAoKoX6hjGo5ij1P76F2qdpFXUUhPJIkahPCCaqqyrdc4RbyXhK3M0nUJoSbyQ1FuIu8l4RwjgQoQgghhPA4trNRCVFEVFVly9ktzDsyj+SMZCLDI+nXoB8hviFFXTXhgnMJ5/ht329Ex0dTyr8U/er3o1apWgUuV1VVNp/dzPwj80nOSKZu6br0q9+PYN9gN9RaCOEpZAyK8CjX0q7xwKwHWPPfGgw6AwoKRrMRX4MvP/f8mcfqP1bUVRQOqKrKB+s+4J2176CgoFN0qKqKUTXyZKMnmdBjAl56r3yVfSX1Cg/MfIB10etyvT+m9JrCw3UfdvPVCCHcScagiGJJVVUemPUA60+vB7QF1TLNmaiopBpT6Te3H6tPrS7iWgpHxu8Yz1tr3sKsmjGpJjLNmRhVbV2jyXsm89Lyl/JVrqqq3P/7/Ww8sxHI+f5IM6bx2J+Pse70OrddhxCiaEmAIjzG5rObWfPfGuvqwTfSKTo+WP9BIddKuMJoNvLe2vds7ldR+WH7D1xKvuRy2RuiN7DhzIY83x8qKgoKH6770OVyhRCeSQIU4THmHp5rd5E+k2pi1alVxKfZX3xNFJ1t57YRmxxr9xij2cji44tdLvvPw386fH8s/3c5yRnJLpcthPA8EqAIj5GckezUIn0pmSmFUBuRH84EBwoKSRlJN6VsFVXeH0LcIiRAER6jTngdjGaj3WNCfENkkT4PVqtULYdBpopKZHiky2VHhkdiVs12jwn1CyXUL9TlsoUQnkcCFOExBjQYYDeFvF7R83TTp+0284uiVSm4El1qdLG5gq9O0VGtZDXaVWnnctmPN3zc7muvV/QMbzYcvc7+6sFCiOJBAhThMUr6lWRSz0koKLlucHpFT93SdXm17atFVDvhrO+7fU+oX2iuYEKv6PHR+zDtgWn5Wgk6zD+Mn3r8ZPP9Ub9Mfca0HlOgugshPIcEKMKj9G/Qn2UDltGmUhvrthCfEF5q9RLrB60nyEfy3ni6qiWrsnPYTgY2HIiP3gfQWk561e7FliFbiKoYle+yBzYayNL+S2ldqbV1W4hvCC+3epl1T6wj0CewwPUXQngGSdQmPNa1tGskZyRTOqB0vhN7eYqUzBRSM1Mp6VcyX60HxVVqZipxqXGE+IZQwruEW8u+mnqVVGMq4f7hxf79IcTtQhK1iSJz+NJhhv41lOCPg/F+35uGExry086fyDRlulxWiG8I5YPKF+ubz7rT6+gyrQslPipBqc9KEfF5BO+seSfPGSkJ6Ql8vOFjqn5dFe/3vYn4PIIxy8dwPvF8EdTcPfy8/KgQVMHtwQloXYLlAsvhpfdCVVXmHp5Luynt8P3Al4CPAugzuw+bzmxy+3mFEIVDWlCE26w6tYpu07thUk3W2TiWGR1danRhwaMLinWw4apZB2bx2J+PoVN0OZKL6RQdTcs2ZfXA1QR4BwAQlxJH28ltORp3NMdMFb2ip6RfSTYM2uCWdWxuRaqqMuqfUXyz9Rv0it76XBt0BkxmExPvm8jgJoOLuJZCCJAWFFEEUjJT6D27t5bWPNtUYfX6f/+c/IcvN39ZhDUsXNfSrjFowSCAXJlPzaqZXRd28cnGT6zbRv0zimNxx3JNozWpJq6mXuXRPx+lGH6XKBQLjy7km63fADmfa6PZiIrKsL+H8e/Vf4uqekKIfJIARbjFrAOzuJZ2zWaeCrNq5ptt3zjMY3GrmLZvGmnGNFTyDipMqokftv+AyWzicsplZh6YaTPFv0k1sSdmD9vPb7+ZVS62vtn2jc1pzaC14k3YMaEQaySEcAcJUIRbbD+/HS+d/e6b84nnuZh8sZBqVLT2x+53mK8lLjWOyymX2Re7z2GCOgWFbee2ubOKt4xt57bZDO5AC/C2nN1SiDUSQriDBCjCLewlWMvPccWdv5e/zdaT7Py8/BwGdqB1ld0uz52rnHlefAw+hVATIYQ7SYAi3KJLjS5kmm3P1NEpOpqUbXLbpCF/oM4DdltF9Iqeu6vcTZBPEM3LNyfYJ9hueQoKnat3dnc1bwnd7+hut7VKQaH7Hd0LsUZCCHeQAEW4RafqnYgMj7R5ozCrZl5tc/tkgW1bqS1RFaIwKLafj9fbvg6Ar8GXF1q+YHMNG72ip09kHyqHVL5p9S3OXmj5gs0BxHpFT4hvCE80eqJwKyWEKDCXApSxY8fSvHlzAgMDKV26NL169eLo0aM5jklLS2PEiBGEhYVRokQJevfuTWxszuXXo6Oj6d69O/7+/pQuXZqXX34Zo9F+H7zwbDpFx5J+S6gcXNn6N2ANWD7q8BF9IvsUWf0Km6IoLHxsIc3LNwe058GgM6BTdHjrvZl8/2Q6VutoPf6Nu95gQIMB1mMB68DP1pVa83PPnwv5CoqPxmUbM6P3DLx0Xtb3nXL9v2CfYJYNWEaIb0jRVlII4TKX8qB06dKFRx99lObNm2M0Gnnttdc4cOAAhw4dIiBAy+cwfPhwFi1axJQpUwgODmbkyJHodDo2btwIgMlkolGjRkRERPDZZ59x4cIFHn/8cYYOHcpHH33kVD0kD4rnSjem8+fhP/nz0J8kZSRRt3RdhjUdRu1StYu6akVCVVXWnl7L3MNzSclMITI8koENBxLmH5bnsVvPbeWX3b9w6topygSUoV/9fnSu0fm2yj6bX+cTzzNx50S2nNuCQWegS/UuDGg4QJZHEMKDuHL/LlCitkuXLlG6dGnWrl3LXXfdRXx8POHh4cyYMYM+fbRvy0eOHKFOnTps3ryZli1bsmTJEnr06MH58+cpU6YMABMmTGDMmDFcunQJb2/HA94kQBFCCCGKn0JL1BYfHw9AaKg28HHnzp1kZmbSsWNW03Xt2rWpVKkSmzdvBmDz5s3Ur1/fGpwAdO7cmYSEBA4ePJjnedLT00lISMjxI4QQQohbV74DFLPZzKhRo2jdujX16tUDICYmBm9vb0JCQnIcW6ZMGWJiYqzHZA9OLPst+/IyduxYgoODrT8VK1bMb7WFEEIIUQzkO0AZMWIEBw4cYObMme6sT55effVV4uPjrT9nzpy56ecUQgghRNGxn+rShpEjR/L333+zbt06KlSoYN0eERFBRkYG165dy9GKEhsbS0REhPWYbdtyZsS0zPKxHHMjHx8ffHwk0ZIQQghxu3CpBUVVVUaOHMm8efNYtWoVVatWzbG/adOmeHl5sXLlSuu2o0ePEh0dTVRUFABRUVHs37+fixezUp4vX76coKAgIiMjC3ItQgghhLhFuNSCMmLECGbMmMGCBQsIDAy0jhkJDg7Gz8+P4OBgBg8ezOjRowkNDSUoKIhnn32WqKgoWrZsCUCnTp2IjIxkwIABfPrpp8TExPDGG28wYsQIaSURQgghBODiNGNFyTvT5eTJk3niiScALVHbiy++yO+//056ejqdO3fmhx9+yNF9c/r0aYYPH86aNWsICAhg4MCBfPzxxxgMzsVLMs1YCCGEKH4KLQ9KUZEARQghhCh+Ci0PihBCCCHEzSABihBCCCE8jgQoQgghhPA4EqAIIYQQwuNIgCKEEEIIjyMBihBCCCE8jgQoQgghhPA4EqAIIYQQwuNIgCKEEEIIjyMBihBCCCE8jgQoQgghhPA4Lq1mLITwHGbVzKpTq9hydgsGnYFO1TvRpGyToq5WsXHiygkWHFlAcmYy9UrX476a9+Gl9yrqagkhrpMARYhi6MDFAzw460GOXzmOQWdAVVVeXfkqbSu15Y+H/qBMiTJFXUWPlZKZwpMLnmTWwVnoFB06RYfRbKR0QGlmPDiDe6rdU9RVFEIgXTxCFDvnE8/Tbko7/r36LwBGsxGTagJg05lN3PPrPWSYMoqyih7t0TmPMufQHEBrhTKajQBcTrlMtxnd2HVhV1FWTwhxnQQoQhQz3279lvi0eGtQkp1JNXHw0kH+PPRnEdTM8+04v4O/jv2V53NnVs2YzCY+WPdBEdRMCHEjCVCEKGam7Z+W5w3WQqfo+P3A74VYo+Jj1oFZGHS2e7ZNqokFRxeQmplaiLUSQuRFAhQhiplradfs7jerZi6nXC6cyhQzV9OuOjzGrJpJykgqhNoIIeyRAEWIYqZ6yeooKDb3G3QGaoXVKsQaFR/VS1bHrJrtHhPoHUhJv5KFVCMhhC0SoAhRzDzd7Gm7+41mI0ObDi2k2jhmNBtRVdWpY01mk8MAoiAGNhpoN7jTK3qGNBlitxvo9mQCbt7rIkReJEARopgZ1GgQrSu2Rqfk/c93SJMhRFWIKuRa5XQl9QpvrHqD0p+Vxut9L4I/Dmbk4pGcvnY617GqqvLb3t9o8mMTDO8b8Hrfi86/dWbFvyvcXq9ygeX4pOMnALkCFb2ip1JwJV5r+5rbz1s8qcBUoDFaRgovoAuwsigrJW4jiursVxsPkpCQQHBwMPHx8QQFBbm1bJPZxOLji5myZwrnk85TKbgSgxoN4t5q97I+ej0/7/qZk1dPEu4fTv8G/elVu5ckdypGTl09xY87f2TjmY0YFANdanRhcJPBlPIvVahlFFRKZgpvrX6LH3f+aB0vEVEigpeiXuKFqBdsBi+FITYplla/tOL0tdM5BvMadAYCvQNZP2g9dUvXBbTgZOhfQ/l598/oFJ219USv6DGpJr7t+i0j7xzp9jpO3zedd9e+y/ErxwHw1nvTt35fPun4CaUDSrv9fMWPCgwGJqN9j7W0nujRWlO+B54pmqqJYs2V+7cEKNkkZyTTfUZ31p5ea/2AtPwuW6IsF5IuYNAZMJqN1u3NyjZj2YBl0mddDEzbN40n5j8BYL1x6hQd/l7+LOm3hDaV2hRKGe6UkpnC0ctHMegM1Amv4xFdEw//8TDzjsyz5hfJTq/oqRNeh31P70NRFOYcmsNDfzxksywFhcMjDlOrlPvH1KiqytG4o6RkplCtZDVCfEPcfo7iazbwiJ39OuAoUKNwqiNuGa7cv6WLJ5tnFj/DhugNQNbNx/L7QtIFAOuHrmX77pjdDJg3oLCrKly08/xOBs4fiEk15fhWb1bNpGSm0G16N4czX9xRhrv5e/nTuGxj6pep7xHBSUxSDHMPz80zOAHt382BiwfYcnYLAN9u+xa9ordZnl7R8+POH29KXRVFoXap2jQp20SCk1y+RWstsUUBJhRSXcTtSgKU6y4kXmD6vul280vkxaSaWHR8Ecfijt2kmgl3+GrrVza7PcyqmeTMZH7e9XOBy/hl9y8FrmtxduDiAYf/hhQUdsfsBmDXhV12jzeqRnac3+HWOgpn7EbryrHFBOwspLqI25UEKNet+W+Ny8GJhYJyUwb0CfdZcnyJzW/1oAUYS04sKXAZS08szXcdbwU+eh+Hx6io1uMcHa+g4GvwdUvdhCu8HexXAHldxM0lAcp1+Q1OQGsqtnfjEkXPmdfX0WvozGucacp0uk63ojvL30lJX/vjsXSKji41ugBwf+37HXZN9azV0231E86618F+FeheGBURtzEJUK67s/yd+X6sWTXTskJLN9ZGuFtUhSiHYx1aV2xtt4xWFVs5LqOS/TJudT4GH15u9bLN/TpFR7/6/SgfVB6AF1q+AOSe8gva81nKvxQDGsgYr8JXwoljZGKAuLkkQLmuZlhNOlbr6PJAQ4POQOOIxjQv1/wm1Uy4w/MtnnfYivJUs6cKXkZT+2XcDsa0GcPwZsMB7d+HgmL9d9W5emd+7JE16LVe6XrMfXguPgYfdIoOBcU6zqeUfylWPL6CYN/gwr+I25797k7t1jG3MCoibmMyzTibcwnnaDO5DdHx0TmyWerQ4aX3It2UjoKCivaU6RU94QHhrB+0nhqhMt3O072x6g0+XP+hdYo4aDdQs2pmyv1TGNDQ8Tf111e+zkcbPipQGbeLfbH7+GX3L0THR1vzBrWp1AZFyd1aEpcSx+Q9k9l6bisGnYHO1TvzSN1H8PPyK4KaC/AHHC2Y2BZYVwh1EbcSyYNSAFdTrzJhxwR+3v0zscmxlAssx9AmQxnQYACzD87mp50/cTr+NKF+oTzR6Ameaf6MJHYqRpaeWMo3W79h05lNGHRakrVRLUfRrFyzQi1DCM8WCRwBbN0eDMAA4PaetSZcJwGKEHacSzjHjvM70Ou0cSeSZC83VVXZeWEn0fHRlPIvReuKrdHr9KRmprI+ej3JGclEhkfelARqwhN8DbyA7QAFYCPQqnCqI24Zrty/iz6zkxCF5FLyJZ5e9DTzj8y3duH56H0Y0mQIn3f6XKazXrfmvzU8s+gZDl8+bN1WrkQ52lZuy5ITS0hIT7Bub1upLZN6TqJmWM0CnTPdmM6fh/9k61mti6dT9U7cW/1eYpJimLZvmjVQ6lu/b4HPVdQyTBl46bzy7OryHEOB34A95M6HogBPAEW73pO49UkLirgtJKYncuekOzkedzzXQFedoqNz9c783ffvIl3DxhOsO72Oe369B7PZjNmJ1Wv1ip5g32B2DttJlZAq+TrnpjOb6DWzF5dSLuGl09a1yjRnEu4fTlxqnPU8ZtWMSTUxpMkQxncf7xGZc511OeUyX27+kp92/kRcahwlvEswsOFAXm71MpVDKhd19WxIAF5BW48n7fq2UsBoYAwyx0Lkh3TxCHGDzzd9zpgVY3IMfr7Rkn5LrPk5bleNf2zMvth9dp+nGxl0Bh5v+Dg/97SfiTcv/179l/rj65NmTHP6nAoKz7d4nnFdxrl8vqJwIfECrX5pxZn4M3kunrhu0Drqla5XhDV0JAE4iNbg3hDHSdyEsE3W4hHiBpN2TbJ7A9Qr+ts+Tf2hS4fYE7PHpeAEtAR20/dNJ92Y7vI5v97yNRnGDJfOqaLy/fbvC33do/wauWQkZ+PP5mq5M5qNJKQn0PfPvnj298QgtO6c5khwIgqTBCjitnA+8bzd/SbVRHR8dCHVxjOdSziX78emm9K5lnbN5cfNPDgTo+p6FuZMcyaLji1y+XGF7ULiBeYfmW/zGk2qif0X97Pt3LZCrpkQnk8CFHFbcDQVXK/oKR9YvpBq45nKlCiT78d66bzylVAtJSMlX+dTUEjKSMrXYwvT/ov7HbYOKSjsurCrkGokRPEhAYq4LQxuPNjuAFiTauKJRk8UXoU8UP3S9akbXjfPtPP2GBQDj9Z7NF+zoGqH187XwGQVlTrhdVx+XGFz5jlRUWUGmRB5kABF3BaebvY0lYMr5znzQ6/oaVe5Hd3u6FYENfMciqIwrvM4FEVxOkjRK3r8vf15864383XOkc1HujzmRafoqFayGndXuTtf5yxMLcq3IMQ3xO4xekV/2w/OFiIvEqCI20JJv5JseHJDrpuaXtHTt35fFvVdhF5neyHA28W91e9l4aMLqRhcMcf2kr4l6VKjS65v+vXL1Gf9oPXcEXZHvs7Xr0E/etzRw2ZAdON2vaLHW+/Nr71+LRZTwp1ZPHFAwwGUDSxbiLUSoniQaca3McssghLeJfDW5290vjvKKGzH446z5ewWDDoDd1e5W24OeTCrZtb+t5bT8acJ9w/n3ur34q33Jj4tnrlH5nIl5QptKrWhRYUWBT5XpimTLzd/yTfbvrEOZo4Mj2RI4yHsv7if6funk2HKQKfo6FmrJ++0e4eGEQ0LfN7CYlbNjFw8kvE7tNwtJrMJvU6P0Wykxx09mP3QbFlzSNw2JA+KsCs2KZaxG8by8+6fScpIwkvnxcN1H+b1tq873a/vjjJE8fLdtu94d827XE7Vpvfq0NGuSjtmPzSbUv6lCly+yWwiJikGg85A6YDS1kyrKZkpXE65TEnfkgT6BBb4PEVlf+x+bfHEhGhK+5dmQMMBRFWI8vCMskK4lwQowqZzCedo+XNLLiReyJU0ylvvzeqBq7mz/J03vQxRvDy/5Hm+2fZNnvsCvAL4b9R/bglShBC3NknUJmx6bulzxCTG5Jk0Kt2Y7lTSqGeXPEtMUsHKEMXH6WunbQYnAMmZyfSZ3acQaySEuB1IgHIbcSZp1MmrJ1n932q7ZSw4ugCjOf9liOLlxWUvOjxm3el1ZBgzCqE2QojbRfFZbUsU2JHLRxxO6dQpOg5cPECHqh1uWhme6PClw0zeM5nT8acp5VeK/g3607JCS48eH3At7RpT90xl67mt6HV6OlfvTJ/IPm7PqXHw4kGHx6ionLx6UsYf3XKuAlOBbWi3i85AH8CnKCslbhMSoNxG/L38HR5jVs34GWzPKHBHGTfKMGVwNfUqQT5BhT6bQVVVXlz2IuO2jMOgM2BWzegUHT/s+IH7at7HrD6zPHKGxdITS+k9uzepmanW6bbT9k3jf8v/x7IBy9y6+Jyvl3MBT7CP85lkE9MTSTWmEuYXdktO71ZVlbjUOAw6g8M8KJ5rEfAwkEpWY/tvaCsZLwMii6he4nYhXTy3kablmlImwH46c52io3vN7gUqQ6/o7ZZhcT7xPM8seoaQj0OI+CKCwLGBPPLHIxy4eMDhY93li81fMG6Ltiqu0WzErJqt3VeLji9i+KLhhVYXZx2+dJj7Z95PamYqKiom1WQdD3Qx+SL3/HoPCekJbjvfwIYDHR4T4hNCuaByDo9bdWoVHaZ2IOjjIMp8XoYyn5fhzVVvkpyR7I6qFjmj2ci4zeOo8nUVwj8Lp+QnJWn6Y1NmH5xd1FVz0QHgAbTgRAVM138AYoB7AM9fakAUbxKg3EYMOgOvt33d5n6domNQo0GUC7R9o3FHGQDR8dE0+6kZP+78kVRjKqCNX5lzeA7NJzbnxX9epN2UdjT5sQlPzH+CLWe3OLg612WYMvhk4yc295tVM7/t+61Ai+jdDF9v/RqzakYl90Bkk2riUvIlpu2b5rbzPXfncwR4Bdg95tW2rzosZ/q+6XT8tSPrTq+zbotLjWPshrHcPeXuYrG2jj0ms4mH/3iYF5e9mGPhyT2xe3hkziN8sO6DIqydq8ahBSZ5DXY3AbHA9EKtkbj9SIBymxl550heb/s6Cgp6RY9BZ7Cmf+9dpzffd/u+wGV81+07x2UsHklMUkyu8Sxm1UyaMY0vt3zJutPr2B2zm+n7pxP1cxRjlo9x6+ygHed3cDnlst1jzKqZJSeWuO2c+aWqKqevnebQpUP8eehPm4OULeYdmee2c+t0OrYP3W4zSBnSeAj/a/0/u2VcSb3C4IWDrS0+2ZlUE7tjdvPpxk/dVueiMH3/dOYdmZcrcLS8x99c/SYbojdw8OJBYpNii6KKLpgPOFplekEh1EPczmQMym1GURQ+6PABgxsPZsqeKdqgUP9S9K3flyZlm+SrjOiEaML8wuhXvx+NyzZ2+PhzCef469hfTtfZcjP+dNOn1C1dl8cbPu70Y+1JM6Y5PEZBceq4m2nu4bm8u/Zd9sXuc+p4FZXUzFS31qFOeB0SXkngi81f8Nu+30gzplEzrCaf3fuZUwNjf9v7Gxkm27N8TKqJH7b/wNvt3i62Y1K+2/YdOkVncxC5gkLbyW2tf3es2pH3O7xPywotC6uKLkh3sF9F6/4R4uaRAOU2VbVkVd5t/26RlLEnZk++zqeg8OnGTxnQYIBbZtdEhkeiV/S5vtFnp6LSsEzRpVX/YfsPjFg8wqUVhg06A03LNnV7XXQ6HS+3fpmXW9teW8aWg5cOWtO72xKXGseV1CuEB4QXpJpF5tClQ3ZnuN3YsrL6v9XcNfkulvZf6oEz3hoCWwBb12MAHH8ZEaIgpItHFLqzCWfz9TgVlYOXDhKXGueWekSUiODBOg/mucIxaIN9a5eqTZtKbdxyPlddTL7IqKWjgNw3N3uMZiNPN3v6JtUqfxyNYbHwxBlTznJmhlt2lsHNgxYMcnlF55tvJLaDE9DGoTxVSHURtysJUEShqxFao0CPN5ltt3i46puu31AhqAJ6JWe3gkFnIMA7gN97/15kuVB+3fur3dadG1mu4fN7P/e4fCQP1HnAbuuJXtHTsWpHSniXKMRauddDkQ/ZDHZtMatmouOjWXVq1U2qVX49AvS7/v/Z3/+WfyfjgFqFWiNx+5EARRS6puWaYlBc711UUKgSUoXSAaXdVpeIEhFsH7qdl1u9TEnfkgD4Gfx4stGT7Bq2i0YRjdx2LlcdiztmzXHijLaV27Ko7yJebOU482tha1upLa0qtMoVCFqYVTOvtX2tkGvlXs+3fB4vnZdLrxlo7+tjccduUq3ySwf8CkwkK9+JArQDlgLPF1G9xO3E5QBl3bp13HfffZQrVw5FUZg/f36O/aqq8tZbb1G2bFn8/Pzo2LEjx48fz3HMlStX6NevH0FBQYSEhDB48GCSkor3FEPhvBDfEAY1HuTSuAqLF1q+4PYWjVL+pRjbcSxx/4sj5bUUkl9L5sf7fqR6aHW3nsdVziQ+U1CI+18cmW9msnrgarrd0a0QauY6RVFY+NhCWpRvAWCd+aWg4GvwZdqD02hftX0R17JgaobVZEm/JdbXzaAz2AzIslNRXUpyV3h0wBC0nCjpQAawEi2brBA3n8sBSnJyMg0bNuT77/Oejvrpp5/yzTffMGHCBLZu3UpAQACdO3cmLS1rJkS/fv04ePAgy5cv5++//2bdunUMGzYs/1chip0vO39pc8Vjy/RlC8v/P1LvEUY0H3HT6qQoCn5efh6T3v7hug877Bbpdkc3Qv1CXe5aKAph/mFseHID655Yx8jmI3my0ZN81eUrzo8+T9/6fYu6em7Rrko7zo4+yy89f2Fw48E81fQpQv1C7T7GV+/rVGLDouWNzKkQhU1RC5BYQlEU5s2bR69evQCt9aRcuXK8+OKLvPTSSwDEx8dTpkwZpkyZwqOPPsrhw4eJjIxk+/btNGvWDIClS5fSrVs3zp49S7lyjrNRurJcs/BcacY0ft37Kz/u/JH/rv1HuH84TzR6gm53dGP6vunMPDiT5Ixk6pepz4jmI3iwzoMuN58Xd92md2PZyWW5xqIoKOh1etYPWu+h01SFxS+7f2HwwsE297/e9nU+6FCckrgJkX+u3L/dGhKfOnWKmJgYOnbsaN0WHBxMixYt2Lx5M48++iibN28mJCTEGpwAdOzYEZ1Ox9atW3nggQdylZuenk56eta8/IQE96XxFkXH1+DLsKbDGNY0d+tZg3sb8Mm9trO83i5mPzSbfn/2Y+GxhdYuMRWVQJ9AZjw4Q4KTYuDJxk+SkJ7AmBVjyDRlYtAZrAHnCy1f4L327+XxqIvAZGArWYv0PQa4NlNIiOLMrQFKTEwMAGXK5FyrpUyZMtZ9MTExlC6dc5CjwWAgNDTUesyNxo4dy7vvFixnh7g1mFUzl5IvodfpCfMLK7LumMKqR3xaPMeuZA2gVFFRUEhMT+TElRM35ZzC/Ua1HMXjDR9n1oFZRMdHEx4QziN1H6F8UPk8jp6HFoxkoiVEU4A/gNfQFukrurw8QhSmYtGp+OqrrzJ69Gjr3wkJCVSsWLEIayQKm9Fs5Jut3/DVlq84k3AGgPql6zOm9Rj61u9baIGK0Wzk6y1f8/XWr3PVo1+Dfg4e7Rqzaqbr9K6ciNMCEUsuFMvvUf+MomrJqvSs1dOp8q6kXuGfE/+QnJlM3fC6tKzQ0ubzZjQbWfnvSqLjoynlX4ouNbq4nKPEHWW4Q/Z6hAeE06VGF3wNzq3Q7E6hfqEMb+5o8cl9aCsIm8haB8fyOw7oCJwEpGtb3PrcGqBEREQAEBsbS9myZa3bY2NjadSokfWYixcv5nic0WjkypUr1sffyMfHBx8fH3dWVRQjJrOJR+Y8wrzDOdc5OXjxIP3n9efw5cOF0odvWQxu/pH5edbjyOUjvN/hfbedb8W/K9h/cb/N/TpFx8cbPnYYoBjNRsYsH8N327/LkW4+MjyS3x74LdcSBwuOLGD4ouFcSLpg3RbsE8yHHT5kxJ3ODVJ2RxnuMP/IfIYvGk5MUlbr7M2ux8GLB/lh+w9sOLMBL50X3e/ozrCmw2y0ltxo3PXfthbpiwOmAc+4q7pCeCy3jjisWrUqERERrFy50rotISGBrVu3EhUVBUBUVBTXrl1j586d1mNWrVqF2WymRYsW7qyO8DBm1czF5IvEpcS5tOjfzAMzmXt4bu5F2K5nuvxw/YfsurDLrXXNy+8Hfs97Mbjr9fhg/QfsvrDbbef7+9jfdmfnmFUzm89uJj4t3m45wxcNZ9yWcbnWwjl6+Sh3Tb6LI5ePWLctOb6EB2Y9kOOGDhCfHs/IJSP5duu3DuvtqIzvtjleTNIdFh9fzIOzHsy1MJ+lHt9vc7wwpqvGbx9P/fH1+WnXT+yL3cfOCzv5cP2H3PHtHU4mY1uA40X6FrqhpkJ4PpcDlKSkJPbs2cOePXsAbWDsnj17iI6ORlEURo0axQcffMDChQvZv38/jz/+OOXKlbPO9KlTpw5dunRh6NChbNu2jY0bNzJy5EgeffRRp2bwiOLHaDYybvM4qn5dlTKfl6HUZ6VoOKEhM/bPcOrx32//3u7sHYPOwI87fnRXdW36YfsPjuux0331sLe4XnbpJtsLux2+dJhJuyblmSrfpJpIM6bxwTqt9UlVVV5cpiV5s5Va//VVr5OSmWLzfKqqMnrZaLtlvLbyNbtluIMz1/LaKvfWY2P0Rp5Z/Awqao7p4SbVRLopnft+v4+LyRftlADauBN7ZJE+cftwOUDZsWMHjRs3pnFjbaGo0aNH07hxY9566y0A/ve///Hss88ybNgwmjdvTlJSEkuXLsXXN6vPd/r06dSuXZt77rmHbt260aZNG3766Sc3XZLwJCaziUfnPMqLy14kOj7auv3gxYP0m9uPN1a94bCMg5cO2l2rxGg2su+icyv9FsSBiwcc18PJFYed0Tiisd08KAARARGU8i9lc//0/dPtBlUm1cSsA7NIzUxlX+w+Dl8+bHfdn8SMRP46ansl6r2xezly+YjDMv4+9rfN/e6wJ2aPw3okpCcw68AszsSfIdPkKDBwbNyWcTZbvMyqmTRjGr/s/sVBKY3JSiefFz2Qd/4gIW41Lgcod999N6qq5vqZMmUKoOVGee+994iJiSEtLY0VK1ZQs2bNHGWEhoYyY8YMEhMTiY+P55dffqFEieK7Boc9yRnJpGbevt94Zh6YyZ+H/yxQ94yjRdgUFAK9AwtW0Tycvnaal5e9TOWvKlPq01KkGdPsHq+gEOjjfD2upl5lzX9rWH96fZ7vkS41ujgso1apWnYDkOj4aIcL0RlVI/Hp8U58u9eu0d5xzpQB8PTfT1Pq01K0n9qeOYfmuH2xPGfr8eTCJ6n0VSXCPwtnzPIxJKYn5vucK/5dYTegNKtmVvy7wkEpz6GNNbFFpWCL9KUC49ECoTCgNvAJcLUAZQpxc9xeWa8KiVk1M3HnRCK/j6TE2BL4f+RPq59bMe/wvKKuWqFzR/fMI3Ufsbt2j4rKQ5EP5buOedl8ZjP1xtdj3JZxRMdHE5ca57A1w9l6xKfFM2ThECK+iKD91PbcNeUuIr6I4M1Vb+Y4x/wj8x2WtS92n916XUq55LAMgEDvQCoEVXB4nIpq9zhnygC4mnaVuNQ41p9ez0N/PMSAeQPcugiks/WwiE+P54vNX9B2ctt8BynOBFmOj+mNll4ecn48W1pVvgPyu9hmPNAGGAHsBa4AR9GmLzcGzuSzXCFuDglQ3ExVVZ5c8CTD/h6WY/Dh1nNbeXD2g3y0/qMirF3hO3TpkMNukb2xe3NsU1WVdafX8cLSFxj21zACvQPx0ue9CJtBMVAxqKJbU6WnGdPoObMnKZkpOTK42usu0Ct6KgZVpE+dPlxKvmSztSUlM4UOUzswZc+UHGNMEtIT+HD9h/Sf2986gPjQpUMOU9hfTbtKXEqczf2WBRAdScpIok54HYJ87E9f1Sk62lZqy+WUy3kGFJHhkTQp28TpjL+W5/f3/b8zfsd4px7jjLql67pUD0tdDlw8wOurXuevo3+x5PgShwOQs2tbqa3dtXd0io67Kt/loBQF+AmYBFTMtq0RsBxwNE3ZnlFogYlKzllCZuAcWasXF0QqWj0XAPby9BiBmWjTpmugBU4TkfE1IrtikQelOJl7eC5T904Fct7QLDfp11e9Tvc7utMw4vZItuTv5U98uu0P+Ru7Ra6kXuH+3+9nw5kN1puzyWzCoDPgb/AnKTMJL50XAJnmTKqWrMqSfksI8A7IVfbJKyeZc2gOCekJNIpoxP2178db7+2wznMOzeFyymWHx2WvR6XgSrSu2Jry48qTkpmCQWegT50+vNnuTSLDI62PmbRrErtjducZ7KiozDo4i6eaPkX7qu3zvKa82OsCiygRgU7ROfzm7u/lT3R8NAnp9rM0m1Uz4Z+HA9oii8ObDWdM6zE56vpZx8/o+FtHW0XkSUVl3JZxjGg+wm05bb7u8jUdpnaw1tsZJtXEt9u+5dtt2mwlX4Mvw5sN5+OOHzt874xqOYrFJxbnuc+yvtTQJkPz2Hsc7YaeAtRDy3EyGrC8FiqwE61rZxlw4yKWGcDc6z+JaMHMMKBqtmPigOnY7j4yAuuB/UB9W5dohxmtq+gTtJYaiw5oAVf2OqcA3YE1aN+RzcApYCPwNVpwtoGs5+M+wCsfdRLFnQQobvbd9u/QK/pca6dYGHQGJuyYwPge7vu26MkeqfsI3237DqNquxvC0i2iqir3/34/m89uBsjRdZFpztTyebTWxgkYdAburX4vXWt0Ra/L+a01JTOF+2fen6u/39/Ln997/+4wb8imM5ucuqn3b9CfQO9AGkU04rWVrzHzwEzrdRrNRuYcmsOCowt4q91b7L+4n+SMZDae2Wi3JcagMzBp9yTaV23Pg3UeZNyWcTaP1St62ldpn2vci9FsZPnJ5ZyOP02oX6jd69AretpX1crYem6r3eu90eWUy3y4/kOWnljK6oGrrUHKgqMLXCrH4t+r/xKXGmd30K8r2lRqw8rHVzJi8Qi7+WTsSTOm8fXWrzl59STzH5mfI3jKNGUy/8h85h2ZR0pmCvVK12N0y9F8ueXLHO8fnaJDp+iY1WfWDblQkoEngdloN2od9qcY/4vW0nCSrJT30UArtBYQi6VogcJnwIvXt+3C8QwhgE3kL0B5Gfgyj+3rgJbXz18x27Hrrv+/+Ybfh4Aocj4fpYHf0YIdcTuRAMXN9sTssRmcgHbz2B3jvlwZnu7ZFs/y066fMBvNuW6UekVP2cCy1u6ZjWc2suHMBptl6RQdW89tZfXA1XbP2X5Ke7ad35Zre0pmCr1m9mLtE2tpW7mtzccnZyY79Y37s3s/I8w/jPtn3s+llEu5XnejasRoNPLqylftBq05HmM2curqKQBaV2xN20pt2XRmU56PNatmXmv7Wo5t8w7PY/ii4cQmZ+X+0Ct6VNQ8r8msmnm97esAlPB2faC6WTWz88JOPtn4Ce+1f4+E9AR+2vWT3SDMHntdJPnRtnJb9j69l32x+4iOj2b6vunMOTzHqdfCwqyaWXh0IatOreKeavcAcCb+DPf+di9H445aX9u/j/2NWTXnCm7NqpkQ3xCqlax2Q8mPAkssR5F1k7YnBm2NnhForSGtyRmcWKjAS2itKA9if2ZQdvl5/k+Qd3ACWoBxDfgIbXDuNeBnbF+r5X2T/fm4DHQFtqCNlRG3CxmD4maOUmgrKAR4Odd0fyuoVrIay/ovs46F8NJ5WbtGqpasyuqBq603xvlH5tsdc2FSTaz5b43dcQHrTq/LMzixUFEZsnCIzf0AGUbH+UcUFPy9/DmXcI6/jv7l8Ibn7A1Rr+gpHaCtVaUoCvMfnU/riq0BrXXFS+eFgoKvwZdpD06jfdX21scuPr6Y3rN75whOLOe23DDzKuPuKncD0KxcMyJK5J3N2R6zamb8jvGYzCZ2nt/pcLaTPV569zflK4pCw4iG3FfrPkbcOcKl4MTCoDMwec9kIGsJgpNXTwJZr61JNdkMBOPT4un4W8dsXWjbgb+xP2PHlh+u//4TOOvg2Beu/24OOFpmQCF/rRRTsR/YGK8fkwnsAGzn7cmbJVi5vcbvCWlBcbuHIh9i/I7xdmdWPFAn94rNt7LWlVpzdvRZ/jj4B5vPbta6Z6rdS7c7uuXonknOSHaqvFRjKsEE57nPknTMnmNXjpGQlkCQb94DQp1pSVBRuZZ2zWGuDVeZVBMDGgyw/h3qF8qaJ9aw6cwm5h6ea11HZ0DDAYT4hmTVR1UZ/c9ou3Xx1fsytOlQMk2Z1C1dl/4N+ucow6Az8Ha7txm+yPWBmJdTLnMl9UqBn4vUzNR8teQ4q02lNnZbpWwxmo2cvnYagGUnl3Hw0kGXzmtSTcSlxPHb3t+up9ifhfbx6yhrbF4sywc4zuqrdQHFA8Fo6fHHkXfrhR5trMeNrTzOOIvjQCv1ej3y+/4woi2imA7Isie3CwlQ3Oy5Fs8xcddEzGreXRph/mE5bkC3C1+DLwMaDmBAQ9vXHhke6XAqb6B3oN0xCpYF/Bw5HX+a+r5597U704qgR0+Ib4jDHC2u0Ct6mpRtkmuMjKIotK7UmtaVWtt87N7YvRyNO2q3/DRTGq0rtuaReo/YPOappk9xOeUy76x5BxUVvaLHaDY6FXj4GnxpWrYpvnpf0kyut6KE+oYS6hfq8uNcoSgKCx5dwIOzH2TNf2sw6AwoKGSa7Y/PsHRHQtYSBI7eq3lZeGzh9QClIHlHLC0hzuV60Y4LRmuBOAIsQgtITGQNUm0EOEoiZ4sz07IVtMG/zdACDFdbUUCrbzJFF6CowGK0gbzb0G6f3dFmR0nX080gXTxuViO0Bov6LiLAK8A6ct/SbRFRIoJVj68i2Dfvb/+3u9qlajs8JswvzG43kNHk3E3DXhBSt3Rdh48PLxGOn5cfzcs3t3bJ5JeCNvCy2x3d+Kf/P/nq5ohJjHF8ENpAVLt1URTeuOsNzrxwhrH3jGVok6E83vBx+49BsQ7WDfYNpk9kH6frbaFX9Iy4c0SuAc83Q0m/kqx6fBVbBm9hdMvRPNX0Ke6reZ/DjLsDGw4EIN2Yn5ur1uqW1f1VHefGnOSl8/XfZe0elcXyXvdGW8dnEXA/WlDSCW0A6ibAuSnpuTnzPVdFm21UEhhI/sa6BF//KQoqMAboAaxCaw2KA2agdZ/NKqJ63dqkBeUm6FC1A+dGn2P6/ulal4ZioGO1jvSO7O3UNNfb1bKTyxzOnvkv/j8S0hNs5utwdjqppQwfQ+5vYzvO70BBsdtqEJMUQ2J6IoE+gbx515s8u+RZp86bXSm/Urxx1xt4673pWK0jd4TdYb2GlMwU/Ax+Tt+wr6Vfc+q47KsL21M2sCz/a/0/QOt6m75vus2ZWCoqdUrVsf594+J8jugVPY0jGjOm9RiXHlcQiqLQokILWlTQFiiNS4mj8Y+NuZB4Idd16hU9bSq1sWb2bVK2CT/v/tnlc+oVPc3LNb/+1xPAm/mpOfD69f9/AVjr4PjqQPZZXjqg2/UfdylxvV6OWtksY7u+BA6iTSu2tOA4erweGEr+Aht3+AttVhTk7M6yvFcGoM2mqohwH2lBuUkCfQJ5utnTTO01lZ/v/5nH6j8mwYkDSRlJTs3isDdWJa+AIy81vq2B74e+tP2lba61Za6lXXOqSyM5U6vHiOYjePOuN3O0mDm6Dp2i44WoF3i+5fMMbz6cO8Lu4FLyJV5a9hKhn4QSODaQEmNL8OSCJzlxxV7CK42zU3NzzyRxbPbB2XaniQMsPrEYVVWJjo9mxSlH6dyzhPmF8Vrb11jzxBqn877cDGH+YWx8ciNtKrfJsV2v6Hms/mMs6rvIGiz2a9APfy9/a8uXs1RUnmpqSVNfDvj0+v/fWI69cseTlVPkPnLnRLmR+1dszq05joOTymS10ASgtUL8ijYLqSLQFOh1ff+N169Hm430qhvqml9fYT84MqMlmhPuJC0owmPULlXbYb9+iE+I3ZtxrbBaHL582Olzbj67mZ4ze/JJx0+sLQaOukEsQn218RKKovBe+/cY3HgwU/dO5fS105TyL0XlkMqMWjoqx+q2lpta+yrteTHqRWtZ5xLO0eqXVpxLOGcdvJlmTOO3fb8x59Ac1jyxhiZlm9isS82wmjb3ZVe/tOs5Lrae24qXzsvuOI3/rv1HXGocRy8fdRjcKSh8fu/nDGg4gFC/0ELp1nFGxeCKrB64msOXDrPt3DYMOgPtq7anXGDOVdaDfIKY2WcmvWb2wqya87ze7C1wBsWAUTXyXdfvrK1kmhfRul/eRUvWBlo3TD+0BQF/QUvQpkfr1nkJaJft8Tq0Voh2aCnruWHfj2R1B91Mfa/XLZm8AxUFeJ6cgYc3WqvDjWPSpgHvkfv5+AS4ueOT7NuK/YHAJrRuMuFOEqAIjzGg4QDGrBhDuinvPn69omdY02F2x2h83ulz5h+d7/Q5LcHAmBVj+Hn3z8QmxTo9m+jUtVPUKlXL+nflkMq81e6tHMe0qtiKzzd9zp+H/yTdmM4doXcw8s6RPNXsqRwtas8tfY7ziedz51IxG0nJTKHvn305POKwzSyrlYIr0bVGV5adXJbn7BQFhcohlXNMS3aWJY+KIwadwekZUGH+YYQHhLtcl8JQJ7wOdcLr2D3GXutJ3fC6+Bh82BOzB52io1O1TrzU6iUbz30/tBv8MbTMqdXIGmfxNFk3fFvnK4OW3Gw5MB8tSKiH1oVUsLFRzgsE5gA90VoSLF8yLN039wHOdoH2R3tO8no+7MlEu525Jwtxbs4E0ZLt1t0U1bLwRzGSkJBAcHAw8fHxBAXZXztEFC9T90xl0IJB6BRdjhutXtFTu1RtNj650eEg4yELh+RrjICrDj1zyOGNLDtLEq8bXUi8QIVxFRyOn1n3xDq7CeZOXjlJy59bci31Wo4uGb2ix0vvxfIBy2lTqY3Nx9uy4MgCes3qZXO/TtHRoEwDdj+1G6PZSMVxFYlJsj1o10vnxfkXz7stY6w7mVUzq0+tZsvZLRh0BjrX6EyjiEY5jklMT6TsF2VJyUzJM3DTKTrG3jOWl1q9hILiIHW/CqxEm0JrSe0+EPC858axA2jjS/4E0oBIYCTa9dyM78KXr5/vJ7QBq4HXz/UyUMnN53oY7TWy1cKrAF+QlXdG2OLK/VvGoAiPMrDRQJb0W0JUhSjrtiCfIEa1HOVUcAIwqeckPmj/AYHegQ6PLYg7Qu9wfFA2tmaJOFpQEbRv7Dcuqnij6qHV2TF0B/0b9re2zugUHT1q9mDz4M35Ck4AetTsQfWS1W3OnjKrZl5p/QqQlUvF3nWMaD7CI4OT/bH7qf1dbTr+1pF31r7D66tep/GPjbl7yt1cTM6a0jt9/3SbwQloz4dlLR/7wclFoAVwL9pNdhrwP6A88JuLtU9BS3H/J7m7ewpLPbRuqXi0acS7gcHcnODkPNqU5U/RghPQpjtPQJud5Hw3r3NGY7uLR4fWyvOEm88ppAVFFJpDlw6x5ewW9IqeDlU7UDHY/oj3uJQ4kjOTiSgRke8BxsfjjnM55bI1Hb07xbwYQ5kSZQpczqYzm2j9i+0cJxaT7pvE4CaDnSozJTOFS8mXKOlX0uEKxc44ceUE7ae251yCllZdRbXmAnmn3Tu8fXdWUKKqKmM3jOWt1W9Zc6mYVTMm1cSQJkMY3328w1Wa3cloNrLy35VEx0cTHhBOlxpdcmV8Ppdwjvrj65OQnpCri8ygGKgTXocdw3bgrfdm6MKhTNk7xeF4qcsvXybMP8zGXhUtONlN3t/KFWAFjjO7moEP0WaYZM9HchfaoE3nxiYVPw+gzazJK2jQo60ntAv3dvlMBoZcL9NyXh1ay81StDWHhCOu3L8lQBE33Zn4MwyYN4C1p7OmRCooPBT5EAMbDWTmgZn8e/VfSgeUZkCDAdxX6z6338CeWfQME3dNzFdyLVuu/O8KJf2yckdkmjJZcmIJ0fHRlPIvRY+aPeyOydh9YTdbzm5BReWNVW9wNc128i6doqP7Hd0xqSbqhddjaNOheOm8+HHnj2w8sxEvnRddanRhUKNB+Bn8+HDDhxyLO0bZEmV5re1r+Uphf6PkjGRm7J/BnMNzSMpIokHpBjzV7KlcXSAWFxIvMG3fNGtg0Ld+X2qE1gC0VoZMU6bTs67ya/6R+Tyz6Jkc06uDfYL56J6PeKb5M9Ztr6x4hc83fW43u+ysPrN4uO7DjFg0gp92/eTwvdS1Rld8Db50qt6J/g36U8K7BKqqkm5Kx0e/EUWxt+KzHmiPNrbEnueBb2w8PhjtJl3ZQRnFzTm0mT+Obl3b0GYYudNJtFaaLWgDeLuhtZzYCkTFjSRAER7jaupVGv/YmHMJ52xOVbV8E7csunZn+Tv5p/8/OdKwF9TRy0dpOKEhGaaMAqdjV1AoF1iOyPBIbZxC9c6E+Ibw8vKXuZRyyTqDI8ArgHfvfpfRUaNzNPWfunqKx/58jK3ntjrMt5Kd5fmx/FZQcozV0Sk6DIqBTHNmrjJ71uzJvEfmodMVba/u9nPb+WTjJ8w/Mh+TaqJycGWevfNZRt450u3ByuLji+kxowdAns/xd12/u57VFcp/UZ7zSedtlqVX9PSo2YP5j85nyfEldJvhXB4Ry2DaUL9Q7qt5HwuOLuBq2lX8vQw83sDE/1qrVLWbHy0JbVpuXo5jv4XEgLZa8o9O1bX4WIq2eKAjPwLDbnJdhKskQBEe46P1H/Hm6jedTqAG2s2ge83uLHh0Qa59qZmpHIs7hl6nDZp1paVl6p6pPLnwSZfqYosOHWYnM4F+1vEzetbuSXJGMsG+wbSd3JaLSRdzBWyWYMWgM6CqKoqiuLXF576a9/F5p89JzkimWslqDsfzxCbFci7xHKX8S1Ep2P6gQ8vrYtAZqFWqVp6vy/wj8+kzu0+u69IpOtpUasM//f9xuNims1RVJfKHSLvTnoN8grjw4gX8vfwJ+CiAlMwUu2W2rdSWdYPWYVbN1B9fn2OXjznMD2OPQQclvGHdE1DfZk/hZWx/O38T+Bj76/n4oo0JuZVyMK3GuUUNpwL2syCLwicBivAYNb6pYV311VUnnj1B9VAtEVVqZipvr3mbH3f+aF0RNqJEBC9FvcQLUS/YTVMOcCn5Eg0mNOBS8iWXV7O1tFg4ynJrS/ZWEktZ9jxQ+wF8Db6kZKaw4GjuIM0dvPXe9K3fl086fpIrVf+hS4d48Z8XWXpyqXVb83LN+bzT59xV+a4cx6ZkpvD0X0/z+4HfrTfrAK8AXmj5Au+2f9f6uiSkJ1D2i7KkZqbanPny3t3v8fpdr+fad6NLyZf4dOOn/H7gd9KMadQKq8U7d79Dx2odrS1Vuy/spslPtvPGWMzuM5uH6j5E/R/qc/DSQZvBjIJCsE8wOp2Okr4l6Ve/HzMOzODElRMutYLdSK9AnXDY9zTkHk9bGm1hwBvf20loA2zfQkux7ihIugh45pTu/ElDyx9je1VzrYvrLFlp/oWnkFk8wmPkd2CqgsLyf7X+9wxTBl2md+GLzV9kW65eSzf/0vKXePrvp3EUZ3+//XuHwYnu+j8Hy021SUQTJt8/mYfrPkzPWj2pG17XqUy3N8p+83IUnOgVPaqqMqP3DCoFV7ppg0kzTBlM2zuNlpNacjnlsnX7gYsHaPpj0xzBCcD289u5e8rdLDm+xLot3ZhO/fH1+W3/bzlaEpIzk/lg/QfW7hWAafum2QxOQBuT8t327xwGgFvPbqXCuAp8vvlzziWeIy41jk1nN9FpWid6z+5tfR9kn3Vji4JiPW54c/srOKuoXEu/xpXUK5y8epL31r3Hmfgz1n2uZpW1MKlw4CJsPXfjHh3a6sPZP6JPoeUJKYmWQXY6joMTb4pu/ZqbxRctyZ2t51yHNi5EgpPiTgIUcVNVCKyQ7w9vSzfA1D1TWXd6nc2b18RdE9l4ZqPdsqbsmWI/OFF0RARG0Lxcc7rW6MqsPrP4u+/fXEi8wJHLRzh06RBHLh9xufXFVSbVREyylkMkw5Th4OiCMapGouOj+XDdh9Ztj/zxiM2ViFVUHpnzCCaz9hy8tuo1u1l3l5xYwt9H/wZgb8xehxljY5JiiEuJs7k/w5TB3VPvtvm8zDsyj/fWvgdAhaAKds8F2vVYjnuy8ZO0rNDSpQA0e0LBgoxrUoDdOZZI0qFlkn0527ZjaNNqnWkxye4+bq3uHYvX0dbmgawEbZZgvhvwXSHWJROYCXQEagBtgElAaiHW4dYkAYoNJrOJ6PhoziWcc/jt3JNcSr7Ef9f+c2rF1eSMZE5dPcW1tGv5Pp+jMoY2HZrndkdUVFqU1xZyG79jvN0gx6AzMGnXJLvlXUm9Yne/WTVTMagi24Zu4+++f1OnVB3qj6/PG6vfYHfMbk5cOWE31bu7GHQGqoZUBaBp2abWYOBmMakmft79M5mmTI7HHefQ5UN2j0/MSGT+kfkADp9zgLfWaJl1nR0Aa++4Lzd9mW014Lx9vulzTl87TUm/kjSOaGy36y/ML4yud2iDLX0NviwfsJznWjznVDZcd1IBX2tDWRngHbS1avyzHTUCrUvD1TEvxeezyzWWVP570J6bB9CmAG9EW7HZPWOZHEtBy2PzGNrYmJPAZrTgqTnaGCKRXxKg3CDTlMnHGz6m4riKVP6qMhXGVaDWd7X4edfPHh2o/HPiH1r93IrSn5em6tdVCf8snNH/jM4zcIiOj2bQ/EGEfhpKtW+qEfpJKD1m9GDn+Z1On+/0tdM5ygj7JCzPMoY2GUpkeKS1+8QZBsVAk7JNaF5emyJ44soJu99QjWYjR+PsJ6dyJjFY2UBt+fpMUyZdp3flWto1twyodYXRbGRIkyEAPFb/MUp4l3DpucuPxIxErqReYdnJZU4dv/DoQoAc3W22WMYf3VfzPrsDfi0rBtvL2TLz4EyH50vKTKLK11Uo/2V54lLjtEyuNoLbb7t+myO/ToB3AF92/pLYl2LZOWwnr7V5zeH53EGv6OlS4yRwFS0B2ZuAX7YjTqHlRMlPsPo3WtK0W1VDtIX8/kRbSLEVNy/dfV5eBNZf/3/zDb+PoGW2FfklAUo2JrOJh/54iNdWvpYjb8KJKycY8tcQXlr2UhHWzrape6bSdXpXtp7bat2WmJHIN1u/ofUvrXMEKf9e/ZemPzVl2r5p1qZyFZWlJ5bS6pdWrP3P0fLtWhnNJjbLUYYZc55l+Bp8qRBUwe6Ml+w3EL2iJ8w/jFl9Zlm3OZptolN0hPrZX0gs2MdxP7zlmPlH5nMu8dxN787JS4WgCtxd+W4ASniX4I+H/sCgN9zUxGY6RWfN0eEMS7DoTNedpd73VLuHRhGNbF6HSTU5DAicaRXM7kz8GUyqKVdwWiWkCn889AeP1X8sz8f5e/nTpGwTAn3ck4nYXiuOTtHxRKMnKBtYDQgh74/kYwU4ewbgOJAU+XEVLXmbrc82E7AYcLwaucibBCjZ/H7gdxYcXZDr27rl7y+3fMm2c9uKomo2XUm9wlN/P4WKmuvbvkk1cfTy0RxjDJ5b8hxXU6/mmh5pUk0YzUYGzBvgsFvh2cXP2i3j8fmPW+syff90/jn5j93yKodUxt/Ln4pBFXm97evsfXqvNaEXwIAGA+yODTCrZh6rl/fNxuJ0/Gm7+yFrFeO1p9fipXN+4S/LTdfSNVMQZxPO5kho17lGZy19ff3+BHgFOJyt5CpLfo8A7wA61ejk1GO61+wOQPWS1R0eawm2dIqOxX0XU7tUbUB7znSKDp2iQ6/oGd99vLW7xZYGZRo4VT8Ly7/bSymXmNl7JgsfXcjmwZs5+dxJ+kT2cfj4jtXsJVKzz3JdPnofetzRgwdqPwBkXbflPdOjZg++6+ZovERBupz80AIf4X7bca51yvGXPpE3Wc04mx+2/2B3KqlBZ2D8jvHcWf5O6zazambVqVX8eehPkjKTiCwVyaDGg9ySudMZ2Vsx8mJSTUzcNZGP7vmI2ORYFh9fbHcmxZmEM6z4dwWda+S9TPvZhLMsObHEbhnR8dEsP7mczjU6O/WcdqjagZ972l7cb+SdI/lx54/Ep8XnmYb8jrA7eCjyIZuPd5blmpxtSVBQ0Ov0NCnbhE87fkq7Ku04cvmINZPsO2veYdHxRS51Exl0BibtnpRj5dv6ZeozuddkJveaDECFLytwLjHXtI8cmpZtSu86vakSUoUZ+2ew5MSSXM+dJdHbm3e9CUDNsJrUDK3JsSu2v7EHeAXQu05vAMZ2HMtDf9h+3hUUvuj8hfXvsoFl2fPUHhYfX8y8I/NIyUwhMjySwY0HUz6ovN3rARh7z1hmH5rt8LgbGXQGVv+3mgk9Jrj0uGblmlEmoAyxybEuPU6v6Bl550i+6vJVju0HLx5k8p7JWmZd/3AGNBxAi/ItHKzXA1pK/AjA9gKMeTOgdTHIKrtFy3OHBng6CVCyOXL5iN2bidFsZFP0Jn7a+RNhfmE0L9+cPrP7sP38dmtyLRWVt9a8xffdvmdY04JnMTx48aC2fo1OW7/mxoRZRy4fwaAz2B3AGZ8ez6WUSxyPO+5wtoFO0XHk8hGbAYqrZTjznB68eNBueeUCy7H2ibU8MOsBTlw5YX2uTaqJOyvcyZ8P/+lwEGa7Ku1YeHShzbro0NG+ihYU3FX5Ln7Y8YPd8iCri2PbuW30n9efZf2XUSe8jrWVYGafmTy54ElmHZxlbS1wlHjNaDZy6uopu8eMaT2G55Y+Z/eYrzp/RZvK2uKA99e+n0HzBzH70Owc9QjzD2P6g9NpVq6Z9XGzH5rNnZPutBn0jrxzJIMWDCI5I5m64XUZ2mQoE3dNzHWcgsLUXlOpElIlx3a9Ts99te7jvlr32a2/hdFsZMW/K6xB39NNn2bCTtcCDWfeY7bMfWQubSe3dTrINOgMlA8sz+ttc+dzqVu6Lp93+jwftTAAbwP2p0LnpEdrOXk1H+cTzmmGNkPK0Wy7uxzsF7ZIgJJNgHeA3fVQAI5dOcZTfz8FZOWsAHLceMyqmaf+foofd/6oZT1V9HSp0YVRLUfRsoJzC0qdTThL/7n981y/ZmLPidbBhCW8Szg1xTHAK8Cp2Qlm1Wz3OFfLCPAOID7dXkIlnFrMrl7pehwdeZSV/65ky9ktGHQG7q1+b46bqz196vSxzj7Js86Y6Vu/LwAP1HmAsiXKcjH5ot1xKGbMmM3ajetC4gU6/NqBYyOPWccu+Hv5M7PPTD7o8AHzj8wnJTOFb7d9myPvyI30ij5X4rQbDWs6jOn7p7Pt3LY8X/tBjQbRulLW4oP+Xv7MemgWH8R9wIKjC6wtFz1r9cy1CGPDiIZsH7qdUUtHsfq/1dbtkaUiScpM4pONn1gX/1t4dCEqKqNbjmZv7F52XtiJXtHTuXpn3m3/bo5uOntUVWXR8UV8vfVr62KS3e7oRqMyjRi3dRwxSVktB8E+wfSu05uVp1Y6PftMp+gI8s1fQsdWFVuxdfBW+s7ty/Erx63bIwIiqBxSOddrEOITwm8P/EZ4gLsToz2FNubhLbQxD/rrv81oU5IPk3OsSTu0WS72MwC711G0Aatz0Ga31ANGAn3R6nurCUVrofoF24sW3sOtu2DjzSeZZLN5dvGzfLf95syfN+gMmMwmJvWcxJONn7R7rHX9msRzub5x6xU9Tcs2ZeSdIzmbcJaE9AQ+3vixzbL0ip67q9zNisdXYDKbqPJ1Fc4mnLVbz3Ojz9m8SZrMJsp8Xoa4VNv5KnSKjgsvXqB0QGme+uspftr1k93rndBtAk81f8ruMaDdyNZHr7fexDpV70T9MvUdPg5gxKIRTNg5we434e+7fW9dQG73hd3c8+s9xKfHWx/jKGOogsL33b63m/TrnTXv8MG6D+wGPnMemkPvyN52ryc5I5kxK8YwcddEa2tHkE8Qr7R5hTGtx7hlrMrZhLOciT9DmH8YfWb34fClwzZTu//12F/0qNkjz332qKrKmBVj+GzTZzmy7DrKuPt1l69pX6U9KZkp/LL7F37e/bPd46fcP4WBjVyfUaGqKq+tfI1PNn6S4zm1dS69oifIJ4idw3ZStWTBxyTlFouWoC0aLTtsX6AqWnbVDWiBQSRaPo7CtBLojnajtrxHdGgBVG+0/C23YpCSBHQGNpF1vZYuu1rAGrSp48JCMsnmk6t9za4wmo2oqAz9ayjH447bPXbCjgmcSTiTZ3eASTWx7fw2Hp//OG+teYtPNn5icyql5Yb6xl1vAFrz+rt3v2vzvAoKw5sNt/sNXqfoHK6XolN0+HtpORz+u/af3WMBLiRfcHjMkctHqD++Pu2mtOO1la/xvxX/o8GEBtwz9R4uJTvOVjvn8By7wYmCwrwj86x/Ny7bmMMjDvN2u7eJDI+kUnAlpwbOZi8jLyOaj6B0QOk8B/3qFT3NyzWnZ62eDs+z+exmpu6dSoYpAx3agMyE9ATGbx/P0cv2p1w7q0JQBaIqRnHq6in2X9xvMzjRKTrGrh+br3MsPr6YzzZ9BuS86TuaQfXGqjeoHlqdFhVaMKbNGHwNvnk+pwadgWolq/Fw3YdzbDeZTSw6toghC4fQ98++fLjuQy4k5n4ffrXlKz7e+DEqWpei5ccWk2oiMT2RD9Z/YLf++VcGGI3WUvE6WnACWt6PjkBPHAcnh4H/oeXueA5t1d+CSAIeREtYlv09Yvn3Nhf4voDn8FQl0PKf/ApEAeWBJmjXuwMJTgpGApRs/jr2100/h4LChB1596GrqorJbOKXPb841edtCXos/93IW+/NjN4zuLvK3dZtTzZ+kk87fmqdTeCl87J+sA9pMoQvO39p95wHLx10OEDTaDZac2WsOb3G4XX8vMv2AFnQFq27a/JdHLl8BNBuApbnZ+3ptXT8rWOuMRP/XfuPl5a9RMVxFQn9JNRuhlLQBsgmZyTn2FamRBneavcWB585yOlRpx2Oc1FRSc5MtntMeEA4H93zUZ4Dcb10XnzV5Su89PYDoaOXj9JjRg9SMrTF7cyYrTfN84nn6fBrBxLTE+2W4YpFxxfZneZsVs1sOrvJqbwoN/pq61f5Wj4gMSORv49pWWqrlazGisdXEOavLarnpfOy1rd2qdqsHrgaP6+svCIxSTE0/akpPX7vwdS9U5l1cBZvrXmLSl9VypF8LsOUwUcbPnK5bkbVyPR90296JmDXmYHn0VpYxgGz0XKHtEBr5chvvpTf0bqX7H1mfQb8AcwH7CdNLH5i0Gbq7ADOAXuv/+145qCwT8agZOMoS6U7mFQTm85uyrFtT8wePt34KXMPzyXdlJ7v1PDZKSikm9L589Cf9KnTJ0ea8Zdbv8zARgOZtm8ap6+dppR/KR6r/5hTYwacWeNEp+isxznzIe1o3M93277jSuqVPL+5mlQT+2L3MffwXB6t9ygAm89s5t7f7iXNmOZ0LhODzkDjiMZ2j2kU0YhNZzbZLNOZMo5cPsJTfz2VZ0CZYcrgwVkPcuzZY3bH5Xy99WstSMvjhmBSTcQmxTJ9/3Sebva03boAXE65zOTdk9l6bit6nTZ+5NF6j1pbwEDLP+LMezLdmA7OJYy12np2a77yzWRfRwegZYWWnHnhDPMOz2Prua0YdAY6V+9Mh6odcsySMatmuk3vxsFL2qDZG8eODf1rKJWCK9Gpeie2ndtmd7yQPemmdOLT4m/CWJSC+Az45vr/W67b8h6aj9aa8mM+yt2GdiuxNQBcRVu4z9KKZUDL+jqOwsv4erOcBFoC18i6fiNa4ri/0Lp4mhdFxW4JEqAUgb0xe/H70I9Q31DaVGrD3MNzMammrGmubpiWZinjj0N/EFUhiheiXrDuyzBlsOT4EuYcmsOpa6cI9w/H38ufIU2GOEyK5swaJ5a08eDc6r3Zb4Z5+XXfrw7X0Zm2bxqP1nuUNGMaPWf2JNWY6tL0XqPZ6PCGPvLOkayPXm9zv9Fs5KmmT5GUkYSfwc8aFManxbPi3xUkZyaz4PACMsx5B21mzMQmx/Lb3t8Y2GigtYwMUwbzj8xn3pF5JGcks+LfFQ5nA03aNQk/gx+l/EvRumJr0k3plPQrmWNQ7F9H/+LhOQ+TYcpAVVUURWH2wdm8uvJVlvVfRsOIhoDW3ZXXTJ3sypYoa23BAEjKSGLCjgn8uPNHziacJcwvjCcaPcFdle7i3bXvsv38du09n88hcCqq9T1m4a335pF6j/BIvUdsPm7VqVXsjtltc79e0fPR+o/oVL0TKZkp+aqbpRxH/5YcO4qWa8MAtCd/3QWWMlTA9lg1LVD5BXgX1xfZc/U2YgQmoCWgW07xbsgfjjZ4+cbPJyPac/44cIjCzW7rDiqQjLbcQtG9PjJINhvDe4YiyR56s1UIrMDpF06jU3QkZyTTZXoXNkRvyJGfRKfoqBRciXVPrKNicEW75bWc1JLt57fbDABK+pbkwosX8DH4EP5ZuMNvoS3Kt2DLkC029weNDSIxw36XhaWMafumMWDeALvHZmd5Dj7q8BGvtrU/JdOsmhkwdwAzDszIc/9dle5iX+w+rqVfw9fgy2P1HsNb783UvVNdap2zBHW+Bl/ur3U/285t49S1U04Fe/b4Gfx4otETvHHXG1xJvULjHxtjMptyBcR6RU9Jv5KcePYEwb7BJKYnUvaLsqRkpuQZPCsoNI5oTHx6PF56L+6peg/LTi7j5NWTOd4jjgYZuyLML4zzL57PNQvJkeeWPMf4HeMdBngJryQQkxRDze/yNwMj0DuQ+Ffic+U4iUmK4VzCOUr5l6JySGUbjz6LNjtkVbZtBrSVjL8n5xo9tuRVhjMmo60EbLEdbeG9jWj5VHqgrbKcfQDwPLQxKPmxCG1xv+LoFFDNiePWoy0gWBzEAJ8CP6N12/kBA4BXyPma558r929pQckmMjyS/Rf3F3U13O5s4lkenPUgAd4BxCbFsila62LKfvMwq2bOxp/l0TmPsnGw/ZWBX2nzCg/MesDm/pF3jrSO18gwOtEP7+CeVSWkit3XRYeOO8LuAGDTmU146bycXtjPrJppW6ktI+8cafOYlMwUUjNTCfENsTteYkP0Bmu3S5oxjSl7puTrhmwJQtKMacw6OCvX9vxKNaYyYccEpu6dSmSpSGvenrzOH5cSx697f+XZFs8S6BPIrD6z6DWrlzX/THYqKntj91q3H718NM9y3RGcWIKcb7t+i9FsJDE9kZJ+Je3OWrqUfIkZ+2cQHR/NlrO2A+HsJu6aSJOyTfJdz8SMRK6mXbUuwXDg4gH+t/x/LD2x1Po8tKrQirEdx3JX5ex5Mq4ArdHW5MnOiDYQ8wywDPvfauNslOGM7IH052grKmfvvjkOfIvWJdTl+rb70G7Up3F9vaAPKb4BymEnjztI8QhQotEG+saS9TqmorWszUYLtOoVao0kQLkuMT0x3/3NxcFfx/5CQbF7kzOqRjad3cSemD00imhk87jJeybb/DavQ+tueefud7RBuA4GfILjlW5blG9hN0AxY6ZDlQ4A+RpwuenMJrrN6MaagWtyjNVZf3o9b615izX/rQG0rih7zf43jglxV2uBO6mopGSmsOPCDofHvbz8ZV5d+SoBXgEMbjKY+qXr2+weyf5euJnXXSWkCgMbDuSTjZ/Qd66Wt8ZX78tzdz7HmLZjWHx8MVvPamNQOlXvxL7Yfby28jXMmF1qwXlx2YvUDqtdoLr+cfAPgnyCCPcPp9esXqRmpuY4/+azm+k1swMbnhxGZPghtCZ1M1oQklc9zWjTef8BblwW4ADwJdqMmiQ7ZThiGYe2Gi04gZxjS0zX6/EgWgtCGbTbyFLgblwPijYDAdd/HgPGYruFaCdZ413uRcvxshTtBvrf9bo8fr1uhZE919klCAp3dez8ewa4SN7dVYlAP7TVowuvu0q6eK77Zus3PL/0ebeUVZwpKHzT9RubLQrnE89T4csKDj/oVwxYwT3V7qH/3P7MPDDTZmCkoPBBhw94ra3theLaTm7LhugNdus8vPlwvu/2PQuOLKDXrF5262bL/Efmc3/t+wGYvm86A+YN8Mgg43bTtGxT3rn7HcL9w9l+bjvPLn02z+MsAYhlOrizrWhFpVYYrB4IZUpodVcUZ95reqAPYFnZOQltkGb+MuXmNh0tt0pPtO4XW+O4dMB7aFOdQWtNuBvtBlcQAWjXkr376wRa8LID7eaoXv8dAVxAe05M2X7fiRbEhRSwLo5kAOXQWqxs8UYL2sLsHOMJooEqOA5qt6I9v/kneVDyYfLuyW6ZPXMrsPc82Gq+z06n6KyzJJ5o9ITdVhsFhYENcyfQOpdwjgk7JvDFpi/Yfm673fOpqNZFHHvU7EG1ktVcbknRK3qm7p0KwLW0awycP1CCEw9xJuEMPWr24I7QO2wGJ5DVcpNpzvT44MSgg3/6Qyl/0Ck4GZyAdgPOPs2/Hu4LTgAsWZ9XYn/asBmtqwm0/CddsH+jdlYyWjeDRSzQFrC03KnZflvy1phu+L0TGOyGujjiTVaAlhcFGIHnBycA+3GuxW3fza5IDhKgXBeTHCM3JLQP+ewL1d0owDvAYRlm1WydmbP5zGa7AY8ZM5vPbrb+nW5MZ+jCoVT6qhLPLHqGMSvGkG5ynJ/h5JWTgJaMbkm/JZQpUcZmAru8mFQT5xO15unPNn12Sw6WLq4sOV1GLB5RxDVxn561oHIIeLncI2kgq3VhDu7PtWHpXnEmh4ulO2cB2jdwd/2buQCsu/7/3wKXXCzbhDZw1/6aVu4xCi1IUdBacAxkZcx9Em3AaXHg5/gQoLCnhUuAcl3FoIq3fQuKQTHQsWpHIsMjc+3LNGVyLO4YwT7BRATYn4Zo0Bmsac8n75lsN/DTK3p+2/ub9e9BCwZZE9VZsnc6I3uSsJphNTky4gjfd/uedlXa0axsM4K97U/51Ct666yKhUcWOnVOUTiMZiO9Zvayu5ZScdOxGmTk635uJGuWzWduq08WV5K1Wf5dr8D9wxl/uf57CvkLfFS0cTQ3mwJ8gDYG5h20oORVtC6vSRSfYZ6tAEfT4g1oaf0LT3F59m66oU2Gsv28/a6EW90dYXcwvff0HNsyTBl8tP4jvtv2nXX9HcvMhLzoFB1DmgwhooQWxNhbswe0louYZG0xuP2x+/n9wO/5qvuNU54DfQIZ3ny4dV2cLzd/yUvLXrIZLJlUE4Mba83Cl1Icp84XhSfTnMmCowuKuhpupVfyM9RQhzbj5Z7rfzteIsJ1ln8f9hKvWVi+qNyM1kbLuQvSbVSYraCVgDcK8Xzu5ou2/IGtLisdMBRt/afCIy0o19UqVatIz1/CuwQtyrcgMjySML+i6bOMKBFBgFdWF06mKZP7fr+P99e9nyPQuJKalapar+gx6AzW1OKP1nuUr7t8bd1fJsBxcilL8rf8BidAjnrnZVjTYdQJr5Pn2BSdoqNHzR50rNYRgBDfkHzXQ2TRKTqqhVTjrsp3yXN6g81ntXEozvMFnkXr1rmZLb2trv9u6+A8OqDD9f+Pwn4wowDV0VoZ1to5LjtLGgPHiSFti3J8iMjmFbQxM5DVVWVpw+iDtv5T4ZIA5bqevzteoO1mCvMLY/PgzRx85mCOG3xhWnd6HUMWDrH+PX3/dJadXGY3I+uTjZ9kUKNBvBT1EvuH72f6g9NzJM+yt/CgRdkSZQE4eDH/g/2qh1an5+89eXLBk6w6tYqTV04yaukoyn5RluCPg+n0WyeevfNZHqzzYI4gxdegTVGd89AczsSfYf3p9Xl2cQnXmVUzk3pOYu0Ta3mkru3srrejWQfgSiqY7CY7fh9tLMVfaAm0viLnWgINnDxbGFAWbXVdW4NeDGhBiWV18BewP2hSDwy7/v+PAiWxfTtRgRfRxs7chRas2BOEtjYQwFN2yrXFcP08hZuzo/jToSXlO4T2+j+EFrDsQFuN2rWkiO4g04yBlf+upONvHd1Qs4JZ98Q62lZui8ls4uE5DzPv8LxCH7iroHDq+VNUDqnMnRPvZOeFnTYDFIPOQP8G/fmu63f8uvdXpuydwoXECxh0BoxmIwadgej4aIfjSAK8AijlX4pLyZdIMeYvvXj2cxrNRnSKLkfeF0vG2N51evN1l6/ZE7MHg85AywotOXXtFM8vfZ51p9c5OItwloLCQ5EPMbPPTBRFYdeFXTT9qWlRV8ujtKkIS/uDn5cOnWL5N2aZKtsX+AEtVb0BLXC4MbfH+8BbLpxRhxYsWKbpqtm2VwA2ANmzSL+JNr4ie3eP5Rv1DLTpzWfRmv0voM3kSSera8VyLf2BqWQFGtFAbbQkYDfSo2WtbXH97yS0lpDDONdlo7t+DRsoWOuLuFkkk6yLFp9YXNRVQEHhw/UfUu9oPSLDI/ml5y+0qtCKr7Z+xdmEs4Val6UnlvJUs6c4GnfUbuuJ0WxkX+w+mvzUhONxx/MdTCVnJpMcb38VYEcsqcstv2+st+XvuYfn0rpia+vaRLsv7Kb5T80xFWp/9a0t0DuQ4c2GUyWkCndOupPT104T7h9O3fC6HLp06KYE3f4Gf4Y1GcYfh/+wrrYd4hvCtbRrLpVTObgy5xLPWd9HfgY/Uo153Ug1NyZ/K1eiHJHhkaw8tdK63VfvS/ea3dl+bjvRCdHWY4/GhbPy39fpWXsLWs6RDLSxDC8Bi4FQsqb6+qKt+/I5WTf6gcDbOJ+QzVKWAaiJFlSEA4PQWiri0WbNpKC1PrwDtENbYHDT9cf1QBsoOZ6sxf8AmgI/oU3x/eN6GQ3QvoE/SM5WkEpoQcpItBlA6dfLvgctKMueUr0E2oye59FWTbYESkHXn4/yaINRzwClr1/LMLQWHVHcSQsK8MyiZxi/Y7wbalYwOkWHXtGTac6khHcJpvaaSq/avYhNikWn6Ij6OYpT1/I3dU53/QMirxVws1NQiAyPpJR/KXae30lSZpLdY730Xh64rLx95QPLM7XXVLz0XgxaMIh/r/5b1FW6Jcx7ZB4lfUtSu1Rt7p95vzU3TWG1ApbwKsGl/13iaupV4tPjqfdDvXxNF3+v3Xu0qtQKg87Aw3MedmoFb9D+jZkx83iDx3m/w/vsvrAbg85A/TL16TO7DzvOa9l7Lc+HTlGoFOzN+kHpVAgyoLVqZJKzdeNGHdBmzViOqY7r02l1aMHHm9f/TkW7qU/Ltt+MdvP/Ha3rx2Ln9b8zyNmiYQlA/sK11PXH0YKLcLSgyN64l0toeTgMaCsE21uTyHi9rilAHVxfANGeK2h5QwxogVlxX5G5cLly/5YABXj676f5cWd+lhm/ebTMkgqrB662rtUx68AsHv3z0XyV93LUy/h6+fLR+o8cfmhbvhW6c3E3cevrWasnIb4hRMdHs+6/dQ6D4ZuhSdkm7By2kxX/ruDe3+7NVxklfUsS9784dp7fSfNJzfNVxg/dfrDOIBuycAiT90zOszVSB7SpBGsHuVL6fOB+tK6Q/K7x0gEtGRtAL2AheQdFPmjp5S3jXaLQFhDM6zNEQRvrEo3tsS4W29ByiGzOtq0u8AlacDSfrJacJ6+X6wwVrRXmA7RxO6A9y73QWoLKO1lOXq4Bo9ECOUsiwBC08Rqv4/iaBUiA4rJmPzVj54WdbqiZe+kVPe2rtmf5gOXWbRN3TuT5pc+TZkzDoDM4nTFz97DdNCrbyGHqeSEKwhOC2r71+hKXGsc/J//JdxmxL8byy55feHWl/RWu86KgUCO0BkdHHuVq2lVKf1ba4b+3/cOhnuPx5Nc1Qsus+gLaoEZH04FtlbHzejnNHBx7H1oAcwStNcKRpdjPl7EVresok5zZarO3HBmy7dMBE8g7O2zq9bpZWmEOknd+GAPaWj07r/92VRLaDKdD5B2ctQT+REt9n1/JaIOiLeN6HuRW7KqSMSguSMpI4sjlI0VdjTyZVBMr/l1BfFo8wb5aEp2hTYfyaL1HmXNoDqfjT7PgyAL2xO5xWJZltd+vunzF9vPbOXHlhN3xJULkR1EHJwAzDswocNLFLzZ/YZ3+7ioVleNXjnM17Sq7Luxy6svAhmhXAhRLl05ivuqn2YM2ENWZBRH/Rlvl2JmuJAW4sctURRu0alnobxK5gxPLcRbZgy4zMARt7Er2VrGpaGNT4skakGuLEa1FZSz5my77I1rwY+szcwva4NyngK9xfbHCSWgBZxLac2RCG7/zFlrit9sziehtH6C8seoNuyvUeoKkjCRrgAJaErJBjbU24cfqPUbt7+1/yDQv19yaor6Ufym2DtnK11u+5sedP3Ih6QLeem+MJmORNMkLcTMUNFD6dNOn9KxZsNQDOkXncB0pC71L9x/LdM9a2F8vx5E9aC0Cjqho3Ru2EzTmPDb7cYfRpqseJOcsIlfp0YILS4Aym6yMuuDcDB8T8DPaQGNXb30TcPxcm68fl0ZWJlxnzEBLgmZhCc7S0bqOvMhaWfr2clvnQUnOSGbSrkke8a3PliCfIMIDbGfvq1WqFv3r97e530vnxfQHc2aHDfEN4e273+b8i+cxvWViaJOh6HXSfypEdguP5X/JgyDvIEJ8Q3IswWBPh6qOj8nS6frvgRRs3IMRbZyHMxS0gamOBoQqZA2SPY82oNbSQm0mf8EJaMHFarT6moEx+SwnCXDuNcnJ2ZmUKjAZOObk8Sa0BGn2vIvW/XP7ua0DlKNxR0nOdM8LX8qvFOH+4QT7OFrPwHl6Rc+QxkNyJD7Ly68P/MorrV/BR++TY3utsFrsfmq3tXsnLzpFx53l7/T41V+FKGwF6SZKzEgkNTMVnWL/I1avQI+aUN2ZxglA+8i2LEBXGm3gp2V7jpKBKk6U58w1KmiDQU+jtQ7YowK7rv//N2gtL+4c75aONkj3v3w+3gtt6rKrXBkLokeb/eSMbWjjZ+xJRpt2fvu5rQMUL52r/YQ2ylG8OP7ccS6+fJEpvaa49FjLB9iNH4Z6RU+N0Bq8cZfj9R0URWFsx7FcHXOVpf2WMuehORx65hBHRh6hbum6Dh//UORDhPqGOvwwFeJ2UpCWVRWVyXsmYzLnfXO2/GtvUAam9nK2VB0wl5wDMZ9Gm/HSONu2Emhp8f9yokxnWmB6oc3mOepMJdG6dQB+xb3BSTm0QCm/6/MY0HK35CcjqiutVTqcr+MVx4e4dNytpUjvSN9//z1VqlTB19eXFi1asG3btkI9f53wOtZF7exx9E3qjXZvWNcaub/W/TzV9Klcj7Pc/JuUbWJdt0ZB4d5q9/JFpy9oXi5rOmOAVwDPNH+GTYM3UdLP+cjdz8uPzjU60zuyN3XCnRltn/W4uY/MxUfvY62bEKJgRiwewSebPslzX60wmHI/bB4MoXZXuo9AG3w5Aq2b4f48jrkfLR35eeAEWr6QcWhjVBw1zZjQZvHY+ozzRctYC863PFiOu+rk8c7QoSV2U3CuZehGerTA5LV8nv85tOfSmSDFhPN1dLZvr5qTx91aimya8axZs3j88ceZMGECLVq04KuvvuKPP/7g6NGjlC5tfzi7O6cZf7n5S15c9qLdY+6ucjfNyzZn4q6JXEu/Zk3I5KXz4tU2r/LO3e+gKFn/wFVVZdq+aYzbMo7dMbvRKTraVW7Hy61epusdXUlMTyQmKYZQv1DC/LMWBoxJiiEpI4nygeXx87L7qXVTHI87zldbvmL2odkkZyQT6BPI5ZTLMttH3JZ06DDoDTclEWHXGrC4n6OjAsnfeIns3gA+xnbekgC0rptX0AZ2mshK1FaVrJT2oI1ZKQ/YS1znjZahNhRthtAxHI87sZzPBy0BnI7cSeDuQpu+bOnGvhOtK8lRC42l7GrXr6WF/cPtOobWArPXwXEG4BxaF5wzWqBNf7b1GpVH69K6NcYJFos8KC1atKB58+Z89913AJjNZipWrMizzz7LK6/YHzTkzgDFrJoZsXgEE3ZMsK7jolf0mFQTDcs05J/+/1CmhDZvPs2YxoIjCzgdf5owvzAeqPMAoX72v6FY1oUpjt0n/137j3o/1CPVmCpBirit6BU9fl5+vNL6Fd5Y7bib1VU6BfY9DbVK2VvV+Ge0JGUFkYyWQn47OWeh6NFufnPR8pyA1gKzGG0gal2gPbkb2X8ga8XbGyloiwJa8pB8hZbYzN4t5gO0ICkc6Ik22+djtO4pM9oCgyPRuqyyj7HbRlYulbwy2v5M1iDgesDdeVxLfqjX69Yf7bnN63PxC7TrdtYOtAAsr+y8yvXzdc1PZT2SxwcoGRkZ+Pv7M2fOHHr16mXdPnDgQK5du8aCBQtyHJ+enk56err174SEBCpWrOi2RG0A285tY9KuSRy/cpxQv1D61utLz1o98dK7Z5xKcbX5zGbun3k/l1IuWcfsZJozqRJShdphtVn2b9Zqxy3Kt2Bf7L481y7xhARenuRmPR/eOm8yzMVr6QFnKCjodXqMZiOhvqFcScvZJ29ZDDIvN66n4+/lj8lsIt2UnufxAOH+4Sx8bCEtyrdg7IaxvLnqTS27sqKgqioqKh2rdeR84nkOXTpkraO91zT7NWiraPfi/Q6L8dbn1UryJvCe7SfEJSlowcL3aEGIHm1cyRi0mTmuUIGPyFoDSI92kzaj5QD5jqxv+ilos3j2krt1QEFbN2cSeXcvmdCCD3uzhnagBQLrs21riBYg5S+LsPNOo2XCXUhWkFIZbcbNwHyUtwstuFuTbVtztMy67fNbSY/k8QHK+fPnKV++PJs2bSIqKsq6/X//+x9r165l69atOY5/5513ePfdd3OV484ARdiWbkxn7uG5bDqzCYPOQKfqnehcozM6RUdcShwXki4Q6hdKucBymM1mpuydwvgd40nOSKZe6Xp83ulzKgVX4tClQ3y/7Xv8vfx5qdVLlClRhkm7JvHW6re4mnYVfy9/nmn2DA3LNOSFJS9wNjn/iyQqKFQJrEJCZgKpxlTaVW7HrIdmcSzuGC0ntsR4PddAsFcwJ0edpKRfSabunsq66HWU8i+Ft96byymXOXTxEHsv7sVkNjm10nLloMpUD61OqwqteP+e90nJTOH3/b/zw44fSExLpGWFlrzc+mXql6nPycsneW/9e3jpvKgTVod/4/8lMSORY3HHOJdwjopBFXmv/Xu0r9Ket9e+zU87fyLdlE7V4Kq83OplygaWJcQnhN/2/4aflx8vR71MSX9tzNLMfTOZc3gOrSu2pnJIZR6e8zCKolgXwQPtpl4lpAoKCievngSwth4CBBgC0Ol0qKpKcmayw4Bqx9AdHIs7Rt+5ffP1mtlSrkQ57qpyF+H+4fRv0J/m5ZpzKfkS32//noT0BNpVaUePmj34Zus3fL31a6LjtQX5Gkc0ZkzrMTxS7xGupV3j2OVjVAutRin/UqRkpjB933Sm7J5CQkYCZQLKUDZIez6jKkbRu05vfAxZ39hjkmKYtm8a0fHRhPuH07d+X6qHVkdVVf679h8pmSk0n9jc7sKCAK0rtmZp/6X4e/lfb1XNQGvF+AVtCmxztBufS/OOnaSiBQ0+FDwF1gW0lO+WDK590dYFulECWiA0hawZQGFoN+MxuKdV41+08TmlcS7xnDtdQBv3UwItOCro9USTdS01CliWZ7rlApTCaEERnifNmEaaMY0WE1tw7Ir9vAKWb6+WbrqOVTsy/9H51gR17lD7u9ocjbM9k0Gv6OldpzezHprltnO6y5azW/h4w8f8dewvzKqZCkEVGNl8JM+3fB4fvQ+JGYnoFT3eem8upVwiwCvAmhzw7dVv8+H6D+1mRPXR+xD/SjzHrxyn/vj6bqu3XtHzUN2H+L23c9M2VVXlcsplDDqDSwPM3aHGNzWsgV5e9Iqeh+s+zIzeMwqxVp4iHi0pnAHtRp6fmTTiVuDxqe5LlSqFXq8nNjY2x/bY2FgiInLPqvHx8cHHxyfXdnFr8zX44mvwZVjTYfxvxf/sjoPpUbMHoGXK7d+gP+2rtM8xcNkdhjQZwpgVY2zWw6SarBl+PU3LCi2Z/+h8jGYjGaYM/Ax+OZ6fIJ+sD4pygTnXE3m84eO8v+59bDHoDPRr0A8fgw/1StejUUQj9sXuc8u4JZNqYlAj559TRVHsJja8mYY0GcLrq163//5w4VpuLcFoCw0K4bwiGbnp7e1N06ZNWblypXWb2Wxm5cqVOVpUhAAY1nQYNcNqoldyj2LXKTq6VO/C/Efns/Cxhfxy/y90qNrB7cGJpR53hN6R51RsnaKja42udKreKY9Heg6DzoC/l79Lz0/10Oq80PKFPPfpFT1B3kG8edeb1m1fdf5KGxhewI8XnaKj+x3d6VitY4HKKSzDmw2nesnqNt8fPe7owT3V7imCmglRPBXZ1JLRo0czceJEpk6dyuHDhxk+fDjJyckMGnS7fsMQtgT6BLJ+0Hrur31/jtwyPnofnm72NPMenVcos6SCfIJYP2g9PWv1zFWP4c2GM/eRucVytpYzPuv0GR92+DBHSwtAq4qt2DR4E1VCqli3tavSjmX9l1GzVM0cx5YPLM/DkQ/nKqNl+ZZ0rNYx13P6TPNn+PPhP4vNcxrsG8yGJzfQo2aPXNcyovkI5jw8p9hcixCeoMimGQN89913fPbZZ8TExNCoUSO++eYbWrRwPE/dndOMRfFyNuEsO87vwKAz0Lpi60IfZ+Bp9ShsqZmprDu9jpTMFCLDI6lVqpbNY1VVZcf5HdrA0oBwWldsjV6nt1lG9ue0TaU21uSHxdGZ+DPsvLDzlrgWIdzJ4wfJFpQEKEIIIUTx48r9W9obhRBCCOFxJEARQgghhMeRAEUIIYQQHkcCFCGEEEJ4HAlQhBBCCOFxJEARQgghhMeRAEUIIYQQHkcCFCGEEEJ4HAlQhBBCCOFximQ144KyJL9NSEgo4poIIYQQwlmW+7YzSeyLZYCSmJgIQMWKFYu4JkIIIYRwVWJiIsHBwXaPKZZr8ZjNZs6fP09gYKBLy8bbkpCQQMWKFTlz5swtu7aPXGPxd6tfH8g13gpu9esDucaCUFWVxMREypUrh05nf5RJsWxB0el0VKhQwe3lBgUF3bJvNgu5xuLvVr8+kGu8Fdzq1wdyjfnlqOXEQgbJCiGEEMLjSIAihBBCCI8jAQrg4+PD22+/jY+PT1FX5aaRayz+bvXrA7nGW8Gtfn0g11hYiuUgWSGEEELc2qQFRQghhBAeRwIUIYQQQngcCVCEEEII4XEkQBFCCCGEx5EABfj++++pUqUKvr6+tGjRgm3bthV1lfJt3bp13HfffZQrVw5FUZg/f36O/aqq8tZbb1G2bFn8/Pzo2LEjx48fL5rK5sPYsWNp3rw5gYGBlC5dml69enH06NEcx6SlpTFixAjCwsIoUaIEvXv3JjY2tohq7Lrx48fToEEDa4KkqKgolixZYt1f3K/vRh9//DGKojBq1CjrtuJ+je+88w6KouT4qV27tnV/cb8+gHPnztG/f3/CwsLw8/Ojfv367Nixw7q/uH/WVKlSJddrqCgKI0aMAG6N19BkMvHmm29StWpV/Pz8qF69Ou+//36OdXKK9HVUb3MzZ85Uvb291V9++UU9ePCgOnToUDUkJESNjY0t6qrly+LFi9XXX39dnTt3rgqo8+bNy7H/448/VoODg9X58+ere/fuVXv27KlWrVpVTU1NLZoKu6hz587q5MmT1QMHDqh79uxRu3XrplaqVElNSkqyHvP000+rFStWVFeuXKnu2LFDbdmypdqqVasirLVrFi5cqC5atEg9duyYevToUfW1115Tvby81AMHDqiqWvyvL7tt27apVapUURs0aKA+//zz1u3F/RrffvtttW7duuqFCxesP5cuXbLuL+7Xd+XKFbVy5crqE088oW7dulX9999/1X/++Uc9ceKE9Zji/llz8eLFHK/f8uXLVUBdvXq1qqrF/zVUVVX98MMP1bCwMPXvv/9WT506pf7xxx9qiRIl1K+//tp6TFG+jrd9gHLnnXeqI0aMsP5tMpnUcuXKqWPHji3CWrnHjQGK2WxWIyIi1M8++8y67dq1a6qPj4/6+++/F0ENC+7ixYsqoK5du1ZVVe16vLy81D/++MN6zOHDh1VA3bx5c1FVs8BKliypTpo06Za6vsTERPWOO+5Qly9frrZr184aoNwK1/j222+rDRs2zHPfrXB9Y8aMUdu0aWNz/634WfP888+r1atXV81m8y3xGqqqqnbv3l198sknc2x78MEH1X79+qmqWvSv423dxZORkcHOnTvp2LGjdZtOp6Njx45s3ry5CGt2c5w6dYqYmJgc1xscHEyLFi2K7fXGx8cDEBoaCsDOnTvJzMzMcY21a9emUqVKxfIaTSYTM2fOJDk5maioqFvq+kaMGEH37t1zXAvcOq/h8ePHKVeuHNWqVaNfv35ER0cDt8b1LVy4kGbNmvHQQw9RunRpGjduzMSJE637b7XPmoyMDKZNm8aTTz6Joii3xGsI0KpVK1auXMmxY8cA2Lt3Lxs2bKBr165A0b+OxXKxQHe5fPkyJpOJMmXK5NhepkwZjhw5UkS1unliYmIA8rxey77ixGw2M2rUKFq3bk29evUA7Rq9vb0JCQnJcWxxu8b9+/cTFRVFWloaJUqUYN68eURGRrJnz55b4vpmzpzJrl272L59e659t8Jr2KJFC6ZMmUKtWrW4cOEC7777Lm3btuXAgQO3xPX9+++/jB8/ntGjR/Paa6+xfft2nnvuOby9vRk4cOAt91kzf/58rl27xhNPPAHcGu9RgFdeeYWEhARq166NXq/HZDLx4Ycf0q9fP6Do7xm3dYAiircRI0Zw4MABNmzYUNRVcbtatWqxZ88e4uPjmTNnDgMHDmTt2rVFXS23OHPmDM8//zzLly/H19e3qKtzU1i+gQI0aNCAFi1aULlyZWbPno2fn18R1sw9zGYzzZo146OPPgKgcePGHDhwgAkTJjBw4MAirp37/fzzz3Tt2pVy5coVdVXcavbs2UyfPp0ZM2ZQt25d9uzZw6hRoyhXrpxHvI63dRdPqVKl0Ov1uUZex8bGEhER8f927iYUtjCMA/jjGmc0G6N8zDSaaSQhUkZqshw7C1mNkpQkNCUJU7KUncLOhgVlRWJD5muhEI1GqfGR2NCsNEQs5n8Xuqc72LilOWfu/1enpve8i/ffU6en5jwnQ6f6OX8yZUNen88nW1tbEgqFpKysTF23WCzy9vYmDw8Pafv1llFRFKmoqBCXyyXT09NSX18vs7OzWZHv+PhYEomENDQ0iMFgEIPBIJFIRObm5sRgMEhpaanuM35kNpulsrJSLi8vs6KGVqtVampq0taqq6vVv7Gy6Vlzc3Mju7u70tvbq65lQw1FREZHR8Xv90tHR4fU1dVJV1eXDA8Py/T0tIhkvo7/dYOiKIq4XC4JBALqWiqVkkAgIG63O4Mn+xlOp1MsFkta3mQyKQcHB7rJC0B8Pp+sr69LMBgUp9OZdt/lckleXl5axng8Lre3t7rJ+JVUKiWvr69Zkc/j8cjp6amcnJyoV2Njo3R2dqq/9Z7xo6enJ7m6uhKr1ZoVNWxubv403n9+fi4Oh0NEsuNZ88fi4qKUlJRIa2urupYNNRQReX5+ll+/0tuA3NxcSaVSIqKBOv74a7gat7q6CqPRiKWlJZydnaGvrw9msxn39/eZPto/eXx8RDQaRTQahYhgZmYG0WgUNzc3AN5HxsxmMzY2NhCLxdDW1qar0b+BgQEUFBQgHA6njQA+Pz+re/r7+2G32xEMBnF0dAS32w23253BU3+P3+9HJBLB9fU1YrEY/H4/cnJysLOzA0D/+b7y9xQPoP+MIyMjCIfDuL6+xt7eHlpaWlBUVIREIgFA//kODw9hMBgwNTWFi4sLrKyswGQyYXl5Wd2j92cN8D7VabfbMT4+/ume3msIAN3d3bDZbOqY8draGoqKijA2NqbuyWQd//sGBQDm5+dht9uhKAqampqwv7+f6SP9s1AoBBH5dHV3dwN4HxubnJxEaWkpjEYjPB4P4vF4Zg/9DV9lExEsLi6qe15eXjA4OIjCwkKYTCa0t7fj7u4uc4f+pp6eHjgcDiiKguLiYng8HrU5AfSf7ysfGxS9Z/R6vbBarVAUBTabDV6vN+0bIXrPBwCbm5uora2F0WhEVVUVFhYW0u7r/VkDANvb2xCRL8+dDTVMJpMYGhqC3W5Hfn4+ysvLMTExgdfXV3VPJuuYA/z1yTgiIiIiDfiv30EhIiIibWKDQkRERJrDBoWIiIg0hw0KERERaQ4bFCIiItIcNihERESkOWxQiIiISHPYoBAREZHmsEEhIiIizWGDQkRERJrDBoWIiIg0hw0KERERac5vq0ZbgC8oUwAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color = ['red' if age > 100 else 'yellow' if age > 50 else 'green' for age in x]\n",
    "plt.scatter(x,y,c=color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2368ebc5450>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "color = ['green' if age > 75 else 'red' if age > 65 else 'yellow' if age > 55 else 'blue' if age>45 else 'orange' if age>35 else 'pink' if age>25 else 'black' if age>15 else 'purple' if age>5 else 'indianred' for age in x]\n",
    "plt.scatter(x,y,c=color)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (1724052468.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  Cell \u001b[1;32mIn[91], line 1\u001b[1;36m\u001b[0m\n\u001b[1;33m    color=[if age > 75:\u001b[0m\n\u001b[1;37m           ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "color=[if age > 75:\n",
    "    color = 'green'\n",
    "elif age > 65:\n",
    "    color = 'red'\n",
    "elif age > 55:\n",
    "    color = 'yellow'\n",
    "elif age > 45:\n",
    "    color = 'blue'\n",
    "elif age > 35:\n",
    "    color = 'orange'\n",
    "elif age > 25:\n",
    "    color = 'pink'\n",
    "elif age > 15:\n",
    "    color = 'black'\n",
    "elif age > 5:\n",
    "    color = 'purple'\n",
    "else:\n",
    "    color = 'indianred'\n",
    "\n",
    "color_list = [color for age in x]\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 4 artists>"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a=np.array(['A','B','C','D'])\n",
    "b=np.array([3,8,2,10])\n",
    "plt.bar(a,b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 891 artists>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 2 artists>"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c=['banana','apple']\n",
    "d=[400,300]\n",
    "plt.bar(c,d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 2 artists>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "c=['banana','apple']\n",
    "d=[400,300]\n",
    "plt.barh(c,d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 2 artists>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z=['banana','apple']\n",
    "d=[400,300]\n",
    "colors=['red','green']\n",
    "\n",
    "plt.bar(z,d,color=colors)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x23690945950>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x, y, c='red', label='Age',alpha=1)\n",
    "plt.scatter(x, y, c='green', label='Fare',alpha=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 2 artists>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z=['banana','apple']\n",
    "d=[400,300]\n",
    "\n",
    "plt.bar(z,d,color=['red','green'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 2 artists>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "z=['banana','apple']\n",
    "d=[400,300]\n",
    "\n",
    "plt.bar(z,d,width=.5,color=['red','green'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class_count=titanic['Pclass'].value_counts()\n",
    "class_count.plot(kind='bar',color=['blue','red','green'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=[1,2,2,3,3,3,4,4,4,4,5,5,5,5,5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1., 2., 3., 4., 5.]),\n",
       " array([1. , 1.8, 2.6, 3.4, 4.2, 5. ]),\n",
       " <BarContainer object of 5 artists>)"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(data,bins=5,color=['red'],edgecolor='black')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "Value after * must be an iterable, not int",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[109], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mplt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mFigure\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      2\u001b[0m plt\u001b[38;5;241m.\u001b[39mSubplot(\u001b[38;5;241m1\u001b[39m,\u001b[38;5;241m2\u001b[39m,\u001b[38;5;241m1\u001b[39m)\n\u001b[0;32m      3\u001b[0m plt\u001b[38;5;241m.\u001b[39mhist(df[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mage\u001b[39m\u001b[38;5;124m'\u001b[39m])\n",
      "File \u001b[1;32m~\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python313\\site-packages\\matplotlib\\figure.py:2626\u001b[0m, in \u001b[0;36mFigure.__init__\u001b[1;34m(self, figsize, dpi, facecolor, edgecolor, linewidth, frameon, subplotpars, tight_layout, constrained_layout, layout, **kwargs)\u001b[0m\n\u001b[0;32m   2623\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39misfinite(figsize)\u001b[38;5;241m.\u001b[39mall() \u001b[38;5;129;01mor\u001b[39;00m (np\u001b[38;5;241m.\u001b[39marray(figsize) \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m0\u001b[39m)\u001b[38;5;241m.\u001b[39many():\n\u001b[0;32m   2624\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfigure size must be positive finite not \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m   2625\u001b[0m                      \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfigsize\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m-> 2626\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbbox_inches \u001b[38;5;241m=\u001b[39m Bbox\u001b[38;5;241m.\u001b[39mfrom_bounds(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m*\u001b[39mfigsize)\n\u001b[0;32m   2628\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdpi_scale_trans \u001b[38;5;241m=\u001b[39m Affine2D()\u001b[38;5;241m.\u001b[39mscale(dpi)\n\u001b[0;32m   2629\u001b[0m \u001b[38;5;66;03m# do not use property as it will trigger\u001b[39;00m\n",
      "\u001b[1;31mTypeError\u001b[0m: Value after * must be an iterable, not int"
     ]
    }
   ],
   "source": [
    "plt.Figure(10,5)\n",
    "plt.Subplot(1,2,1)\n",
    "plt.hist(df['age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y=np.array([10,24,34,77])\n",
    "mylabels=['apple','mango','banana','peach']\n",
    "plt.pie(y ,labels= mylabels,startangle=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y=np.array([10,24,34,77])\n",
    "mylabels=['apple','mango','banana','peach']\n",
    "mylllabels=[0.2,.1,0.1,0.1]\n",
    "plt.pie(y ,labels= mylabels,explode=mylllabels,shadow=3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y=np.array([10,24,34,77])\n",
    "mylabels=['apple','mango','banana','peach']\n",
    "mylllabels=[0.2,.1,0.1,0.1]\n",
    "plt.pie(y ,labels= mylabels,explode=mylllabels,shadow=3)\n",
    "plt.legend(title='fruits')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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XXnsts2bNoqioqG9B1pEqKSnB5/OxceP+S0cqKyuDfsAtKyujoaGBhob9/Tx37NhBT08P5eXlR/9GhEGNm/CaNClwseWBG0NLB+kkkJSURFJSEitXrsTtdtPS0sJf//rXAc/x4osv8u6777Jz506uu+46uru7Oeecc4Ke695772XLli243W7+/Oc/k5KSwpIlSwZ93TvvvJNnn32Wu+66i+3bt1NRUcELL7zA7bffPty3DgRGWg3WBip7Kul19x7VcwnDW6zhctjwej1odPt7yI/L8NrH1Qsf3w2PzIKvngb/4IuUQqW4uJivv/6a999/n927d3PHHXcM+RxUaWkpS5cu5eqrr2b9+vVs3LiRq6++GqPR2PfZsnTpUqZNm8bFF1/MN998w/r167n00ks54YQTmDt37mi8NYFxFF5DXWquUqm4//772bVrF8cccwy33XYb999//4D73XDDDfzlL39hxowZfPbZZ7zxxhtB890AP/3pT7n77rs57rjjaG9v56mnnhowFbHP8uXLeeutt/jggw+YN28eCxcu5MEHHyQvL29I9e8jKzLtjnYqeyqxuC2Hf4BwRIY18rJZURS5bwStld1oGF/Nigdla4W3fx5Ynbj15VBX0+eaa67h3HPP5aKLLmLBggWYzWauvfbaIT/Ps88+S0ZGBscffzznnHMOV111FXFxcX3T/JIk8frrr5OUlMTxxx/P0qVLKSws5MUXXxzptyT0IykHDlWGyOVyUVNTQ0FBwYies9m1axd2u520tDTS0tKw2+3U1dWRk5NDYmIiW7ZsISMjg7S0NJxOJ42NjbhcLsrLyzGZTFitVnbt2sXMmTPRaAKn9hwOBzt27GDatGno9XoqKyvxeDzk5+cDgcUdVquV1NRUZFmmoKCAF198kRNOOKHvRDDA9u3bSUpKYvfu3Zx44ol88sknTJ8+HZPJRG9vLy0tLSiKwqxZo3uxp81jo8Xegsc/cCGG7JVpb2znvsr7aPG0jGod49H1s67n6ulXD+kxG9a8z4cv/53c4ikAxPvNnNHzzChUF+byjoHTH4D00lBXMioaGxvJycnho48+4uSTTw51OVErrBdspKSkIMsyFRUVQGBhRGpqKpIkkZ+fT1NTE21tbZhMJiZOnEhlZeWQnj8nJ4fa2lp27tyJRqMhMzNzWCdq09LSqK+vR5ZlEhISyMrKorm5ecjPc6S8fi+t9lYsHjHSGi3DbQ3V/2dBw3ieMjyUurXw+LGweAWccAtojYd/TBj73//+h81mY9q0abS0tHDzzTeTn5/P8ccfH+rSolrYhldJSUnf/w82pZaSkkJKSkrQsf7zy3FxcQPmm00mU9AxvV4f9DpA36rC2tpaACZPnhw06oLA0loILLWHwIrGxMTEoPsc+JiRoCgKZpeZdkf7gHN7wsgazrSh3dKDqt9K13F9vutwZC989iBs+y+c9keYvDzUFQ2b1+vll7/8JdXV1cTFxbF48WL+/e9/H/TUgDA2wja8Qi0/P/+wAbFkyZIxCxG7106zrXnQKUJh5A2nNZSlu3P8XeN1tHrq4LkLofQM+Nb9kJAd6oqGbPny5SxfHrnhO16NmwUb45VP9tFobaS2t1YE1xgazsjL2tuNVtt/peE4usbraO18Cx6bD58/CuLyDWEEiPAKY12uLvZ07xFL38eYRtKQYkg5/B378XrcuBw2NP2mksTI6wAeG3zwK/j7qWAe2vVWgnAgEV5hyCf7qOuto8XWgqyIK/3HWrIx+aDXBx6M0x7ortH/Gq+oXbBxOI3r4fHjAk1/BWGYRHiFGavHSmV3JTavmHIKleGuNPR5D+iuEYkd5ceK1x5o+vvvC8AWnTt1C0dHhFeYkBWZJmsT9ZZ6/Io4JxBKw+6u4fGgGS8d5cfKng/gr8dA5UehrkSIMCK8woDb56ayu5Ied0+oSxGAVNPw+hrKsh+VKrBUXq140SnukS5tfLK3w7/Oh/d/FXYtpoTwJcIrxLqd3VT1VOGVxT/acDGsaUOHHUna30tTnO8aKgW+eBT+tgx6Gg5/dyHqje51Xr8Z2n5IR/dakbUiT1ZkmixNWLyiS0a4GW5H+f6X/Ikpw2Fq3ghPLoELn4X8Y0JdjRDGxMgrBNw+N1VdVSK4wtRwRl52Sy9Svy1txDVeR8HRCc+eFehULwgHEdXhtWTJEq6//npuvPFGkpKSyMjI4KmnnsJut3P55ZcTFxdHUVER7777LhDY8fjKK6+koKAAo9FISUkJDz/8cNBzXnbZZZx99tn86U9/Iisri5SUFK677jq83sC0YI+zh3U713Hld65kTs4cls9ZztuvvM0ps0/hn4//s+95WhpbuP6S65mXN48FBQv4+ZU/p7O9c+z+cKLYcLprWHtEd40RJXsDnerfvFGcBxMGFdXhBbBy5UpSU1NZv349119/PT/+8Y+54IILWLx4Md988w2nnHIKl1xyCQ6HA1mWmThxIi+99BI7duzgzjvv5Je//CX/+c9/gp7zk08+oaqqik8++YSVK1fyzDPP8I9//INWaytN9iZuXXErHa0d/OO1f/Dg3x/kpWdfoquzq+/xsixz/SXX09vdyzNvPMNTLz9FQ10DN11101j/8USl4XfXEOE14jb8A1Z+G2wdoa5ECDNRH14zZszg9ttvp7i4mNtuuw2DwUBqaipXXXUVxcXF3HnnnZjNZrZs2YJWq+Wuu+5i7ty5FBQUcPHFF3P55ZcPCK+kpCQeffRRSktLOeOMMzjttNN46723MLvNVO+pZt3qdfzmwd8wfc50ymeUc/eDd+Nyuvoev27NOvZU7OG+J+5jyowpTJ8znd8/9nu+/vxrtm7cOtZ/RFFFQiLFOLTuGn6fD4fNErxMXlzjNXLqP4enToSWzaGuRAgjUR9e06dP7/t/tVpNSkoK06ZN6zu2rzt8e3vgQsrHHnuMOXPmkJaWRmxsLE8++ST19fVBzzllyhTUe7uLe31eYpJiaOtoA6C2shaNRkP59P3bg+cW5hKfGN/3++rd1WRmZ5KVndV3bFLJJOIT4qneXT1Sb10YRJIhCa1qaN3CnXYrPo/7gGlDcc5rRPU2wN+Ww/bXQl2JECaiPrwO3NZAkqSgY/uWPsuyzAsvvMBNN93ElVdeyQcffMCmTZu4/PLL8Xg8gz6nw+WgprsGv+Qf1j5hwtgb1kpDhw2f1xvUlFcslR8FPie8fDlseCbUlQhhQGyJMgRr165l8eLFQVuJV1UN3mDU6rDSZG/CLwV3y8gvysfn81GxtYIpMwL7gtVX12Pp2b/ysHByIa1NrbQ0tfSNvqp2VWHptTCpZNJIvy2hn+G2hvJ6Dxx5ifAaFYoMb94Aji447mehrkYIoagfeQ1FcXExX3/9Ne+//z67d+/mjjvu4KuvvhpwP6/PS6O9cUBwARQWF7LwhIXc9bO72PrNViq2VPCbn/8Gg9EAe3vBLjphEcVlxdz6o1vZsXkHW7/Zym3X3cbcxXOZOnPqaL/NqDackZfLYcPv86HWBH4WlBQ/esU50qUJ/X18F3xwe6irEEJIhNcQXHPNNZx77rlcdNFFLFiwALPZHDQKUxQFl8eFy+9Clg4+Tfj7R39PSloKP/j2D7jhshs4/5LzMcWa0BsC006SJPGXf/6F+MR4fvDtH/DD835ITl4Of3rqT6P+HqPdcJbJO+2B81v7ppiNsp2h9aQXhuXzv8DrK8T+YFFKUo5yK2CXy0VNTQ0FBQUYDIaRqiviyLJMe287Zp+ZoX5ytTa3snTGUp5+5WkWHr9wZOrxyrQ3tnNf5X20eFpG5Dmjwa3zb+XisouH9Jh1H73Bqjf+TW5xYBo4xdvCcstzo1GeMJiyM+G8v4FGf/j7CuOGOOc1Avyyn5buFnqV3iMKri8//RKH3UFxWTEdbR08cNcDZOdmM2fRnNEvVjikYXXXsAa3JjOIZfJjq+LNwNYq33kO9LGhrkYYIyK8jpLP76OluwULR97qyef18fC9D9NY14gp1sTMeTO57/H7Bqx8FMbecKYNbb1dYrFGqNWshn+fD9//L+hMoa5GGAMivI6C1+ultacVizS0HoXHnHQMx5wkmo6Go2F11+gxi2u8wkH9F/DixfDdF0GjO/z9hYgmFmwMk9vjDoy4hhhcQngb6rShLMvYrb1i5BUuqv4XuBZMLOIY90R4DYPL7aK1qxWbJH7CHk/itHEYNENbdORy2PC6xTVeYWXnW/DatXB0a9GEMCfCa4hcbhft3e3Y1XYUSfzjGE+Gt4OyDZ/Xg7ZfX0PRXSMMbHkB3hGNrMczEV5D4PF66OjpwKa2ieAah4bfXcMjRl7h6Kun4cNfh7oKYZSI8DpCXp+Xjq4ObJIIrvFquN01fP3DS1HEUvlwsvYhWCMu7h+PRHgdAZ/fR2d3JxbJgqwSDXbHq+GNvIK7axgUByrEDzdh5X+/hU3iovHxJqrDa8mSJdx4442HvI/f76ezu5NeuVcE1zg3nGu8XA5bX3CBON8Vtt68Eeq/DHUVwgga1eu8pq2cdvg7jZCtPxj5TRplWcbcY6bH14NfI5bejnfDGXk5bBb6d1gT57vClN8duAbsqk8gMSfU1QgjIKpHXociyzJdPV30eERwRYvhjLysvd1o+nVGERcohzF7Bzz/XfCIHzDGg6gPL5/Px4oVK0hISCA1NZU77rgDWZbptnTzzD+f4ZxvncP8/PmcUH4CN19zM+YOc99j169dz9S0qaxbs44Ll17I3Ny5XHzaxdRU1vTdp76mnusvuZ7jy49nXt48Llp2EV+s/iKohlNmn8KTDz7J7T+5nfn581k6cykvPftS0H0euPsBTl9wOnNz53Lq3FP5y+//gtfrHd0/nCgzrO4a3Z1ipWEkadsK/71aXAM2DkR9eK1cuRKNRsP69et5+OGHeeCBB3jk0UfotfXiwsX1t17PK6te4ZFnH6GpoYnbrx+4h9Ajv3uEX9z1C1788EU0ag13/OSOvtscdgfHLT2Ov73yN17+38sce9KxrPj+Cloagzu9r/zrSqbOnMrL/3uZ71z+HX77i98GhWBMTAz3/OUeXv/sdW6991Ze/ufL/PPxf47eH0wUGuq0oaIo2Hq70fTbQVmEVwTY+RZ8fHeoqxCOUtT3NszJyeHBBx9EkiRKSkr4esPXPPboY5z63VM55+Jz9t8vP4fbfncb31n2HRw2B6bY/c0/f/LLnzDvmHkAXPmTK7n2e9fidrnRG/SUTi2ldGpp332vv+16Pn7nYz557xO+98Pv9R0/bulxfOeK7/Q9x7NPPMv6z9ZTUFQAwDU/v6bvvtm52Vx23WW8++q7XHH9FaPzBxNljBojsbqhdSR3Ox14PK6gaUOxTD5CfPYApJfB9AtDXYkwTFEfXgsXLuxbLeZwOSifWs6jf3kUj+xh57ad/N/9/8eu7buw9Ow/Md/S1MKkkkl9zzG5fHLf/6dlBH567+rsImtiFg6bg8f++BhrPlxDZ1snPp8Pt8tNS1PwyKv/c0iSRGp6Kl2dXX3H3n31Xf791L9pqG3AYXfg9/uJjRPbP4yU4UwZOh02vB4PsQkxfcfEOa8I8sb1kDoZJswMdSXCMER9eO3j9Xnp6unCLwUWZ7hdbq658BqOOfEY7vvrfSSlJtHS2MI1F16D1xN8rkmj3f/HuC8IZTmwrP6Pv/kjX6z+gpt+cxO5BbkYDAZ+esVPBzyHVhO8HYqE1Pccm77axK0/vpVrb76WY046hri4ON597V1W/t/Kkf1DiGLD7a7hE901IpfPBS9fAdesEfuARaCoD68vv/yyb2Wh2+dmw6YN5BbmUlNZQ09XDzfecSNZ2VkAbN+0fcjPv2n9Js7+ztksPX0pAA6bg+aG5qE9x1ebyMrJ4pqf7Z86HOpzCIc2It01EOEVcbqq4J1fwDl/DXUlwhBF/YKN+vp6Vly/gq3btvLa26/x76f/zfev/j5Z2VlodVqee/o5Gmob+OS9T3jiz08M+flzC3P56K2P2Ll1Jzu37eTmH93cN6I6UnmFebQ2tvLOq+9QX1PPv578Fx+/8/GQaxEObjjL5J12G4qioFIF/hnpZCdqxGUVEWfzc7DlP6GuQhiiqA+v737vu1gsFs759jncfevdfP/q73PBpReQnJrMvX+5lw/e+ICzjj2Lpx95mpvuGnqX6pvvvpn4xHi+f/r3WfH9FRxz4jGUTS8b0nOceOqJXPKjS/jdrb/j/BPPZ9NXm/jRz3405FqEgxvWyMsefH5LjLoi2Fs/g66aw99PCBuSohzdBQ8ul4uamhoKCgowGIa2F1KoeTwe2sxtuHHj1rpDXc6Ikr0y7Y3t3Fd5Hy2elsM/IMrdc8w9nFV01pAe89k7L/Hpuy+RN3kqABmeOk62vjwa5QljIXsOXPE+qLWHv68QclE78vLLfsy9Ztz+8RdcwtANZ8GGpacLtXr/aWOjWCYf2Zo2BJr4ChEhKsNLURR6entwupz49L5QlyOEgeFsRGnr7UKj679YQyyTj3hrH4Gq/4W6CuEIRGV42Rw2LHYLil7pWxovRLfhdNew9pjFSsNxR4HXrgWXJdSFCIcRdeHlcrvo7u0GFbhVYrpQAI1KQ6I+cUiP8XrcuF1OtCK8xh9rC3z0m1BXIRxGVIWX3++nq7cLv9+PV+dFEZsGCgRWGvbfk+tIOO1WvB530MhL7OU1jnz9d7H/V5iLqvDqtfXicruQ9BJeREd2IWC4Oyj7vF40OtGUd3xS4M0bwC8+J8JV1ISXy+3CarOi1qhxqByhLkcII8Pqa2i34vO6DzjnJRZsjCsdFbD2oVBXIRxEVISXLMv0WHrwy368GjFdKAQbzsjL5Qh011Cr1QBoFA/aURzNr6nzcebzDib82Yp0l4XXdg58rYoOP99+3kHCHyzE/M7CvKds1PceuptLj0vhuredZP3Ziv4eC5P/YuOdPfuf+99bvOQ8aCXpPgs/e98V9NjaHpnJf7FhcY/jf09r/gTmqlBXIQwiKnob2hw2HC4Har0ap+QMdTlCmBnOMnmn3Qb9fgga7SlDu0dhRoaKK2ZqOfc/A7+Hq7pkjv2HgytnablrSQzxeontHX4Mh/gX7vErLPunnfQYFS9fYCQ7XkVdj0yiIXD+r9Mh88M3nTxzlpHCJBWnP+fgpAI1Z0wOXMR77dsu/rBUT7x+aOcLI4rPFZg+vOytUFciHGDch5fH66HH2oNarcapCq/gaqpvYvmc5bz8v5cpnVZ6+AcMwtfrw+/wI3tkkEBlUKFNCu4Q0PRME7btNnw9PlQGFaYiE5kXZKKfoD/Isx5Q5zNNdK/qJvO7maQuD3zQy16Zpr83Yd1oRZOgYcKlE4idsr8zd8c7HXjNXiZcMmFY72ssDXfkBfs/tEd7sca3irV8q3jf3+vA7+Nf/c/FacUa7l+2v8vNpORDT6z8faOXLqfC51cY0aoD7yU/cf9jqrsVEvQSF00NvO6JBWoqOmTOmAzPb/WiVcO5ZVHQjaL2U9j4b5h1cagrEfoZ1fCqKB1aD7+jUbazYsAxRVHosfTg8/nAAP5x2DTV7/KjjlOj1WtBAW+3F0+bB236/g8VY76RxEWJaJO1+O1+2l9rp/ZPtUz+02Qk1aF/arZssOCscqJJDP5W6V7VjavOReEdhdi22Gh4vIHSR0qRJAlPh4fu1d1M+s2kgzxreBlOeFl7u4NWKIbyfJesKLy9x8fNi/Us/5edjS0yBUkStx2r5+zSg4fLG7t8LJqo4bp3XLy+y0eaSeJ707TccowOtUqiOFmFw6uwscVPXqKKr5r8XDFTR7dT4Y5PXHzyg5iDPve488HtUHo6GBNDXYmw17g+52V32rE77Wh0mnE7XajP0KOJ1aDSqlDpVOhSdSg+BTz775O8JJmYkhh0aTqM+UYyzsvA2+XF0+k5+BMTCMLmfzUz8UcTkdTBIeducRM3Mw5DtoHkk5PxW/34rYEfDppXNpN5YSZqo3rE3+9oGHZ3DW14rDRstyvYPPCHtW5OnaThg0tMnFOq5dwXnayuPXgHmepumZd3ePHL8M73TNxxvJ4/f+HhnjWB74sko8TKs41c+pqT+U/ZuHSGluVFGm76wMWK+TpqemRmPWFj6v/ZeHnHOF+V5+yCzx4MdRVCP+N22tDn99Fj6UFCwqV2DXqfy866jOLSYgDefOlNNFoNF112EStuXREYQbg9PPy7h3n3v+9itVgpKi3ip3f+lPnHzAegp6uHe2+9lw1fbMDSayEnP4erbryK0849re81ZFnmmcee4aVnX6K1uZWUtBQuuPSCoL25GuoauO+O+9j6zVZyC3O58493MnPezGG9774+ywf5sUR2y3R/2o02TYs2+eA/lSuyQuOTjaR+KxVD9sCGy4YcAz2f9yB7ZGxbbWgSNajj1PR83oOklYifEz+s+kNhWCOvHvMBraFCF17y3r/ys0o0/HRRIFBnZqr5vMHP4xs8nJA/+D9zWYH0GIknzzSgVknMmaCmySrzx889/HpJ4HnOKdNyTr+pwdW1Pra0+/nLaQaKHrHx/HlGMmMl5j9t5/g8Nekx4/jn4S8fh/lXQ0J2qCsRGKfhpSgKvdZePF4PGr3mkNd0vf7i65x78bk8/8HzbN+0nbt+fhdZE7M4/5LzuffWe6naVcUfn/wjaZlpfPzOx/zooh/x6upXyZuUh9vtpnxGOVdefyUxcTGs+XANt117Gzn5OUybPQ2Ah+55iJf/+TK3/PYWZi2YRWdbJ9V7qoNqeOR3j3DTb24ib1Iej9z7CDdfczPvrH8HjWbofz1esxeVXoWkDR4pmT820/afNmS3jC5TR/4v8lFpDv5B0/lOJ6ggZVnKoLcnHZeEq8HFnl/uQROnIefaHPx2P22vtlFwawFtr7TR+2UvunQd2VdmDzgPFy5UkooUw+Dv8WB8Xi9Ouy1sumukmiQ0KihPCx7plqWq+Kzh4FPlWXESWpWEut/UcVmqilabgsevoDtwtO1TuPYdF/88x0hll4xPpi8YJ6eo+LLRz5kl4zi8fC745F44+/9CXYnAOA0vl9uF1W5Fq9Ee9pquzOxMbrnnFiRJoqCogD079vDs489yzInH8Nrzr/Hhpg9Jz0wH4PLrLmft/9by6vOvcuPtN5KRlcHl113e91wXX3Uxaz9Zy3uvv8e02dOw2+z868l/8cvf/5KzvhPYbiO3IJfZC2cH1XDZtZdxwiknAHDdLddx1rFnUV9TT2Fx4ZDet9fsRfEq6LP0KHLw8uXERYnETonF1+uj891OGh5roPBXhah0Az9snLVOzB+YmXTXpIN2npA0EhMuDV6M0fh0IynLUnDVu7B8Y6Hot0V0vNNBy79ayL0+d0jvZawk6ZNQq4Y2vem0W/F6PRiM+8/5GJTQnfPSqSXmTVCzyxy8LH53l0xewsHPaR6To+a5rV5kRUG19+95t1kmK1YaEFwA96wJTEvOzlKzscWPr9/3mNcP/nG8Yr7P5udh0XWQMSXUlUS9cRde+67pUhQFRaPg49Bd46fPmR70AT1j3gxW/nUlu3fsxu/3c/qC04Pu7/V4SUhKAALtpp566Cnef/192lra8Hq8eD1ejEYjANW7q/G4PSw8fuEha5g8ZXLf/6dmBM6/dHV0DSm8vGYvfqcffaYeSS0NCC+1SY3apEafqcc4yUjFtRVYvrGQuDBxwHPZd9nxWX3s+vmu/QdlaH2hFfMHZkr+XDLgMbYKG+4mN9lXZNP6Yitx0+NQ6VUkzE+g5qPw3eRvODsouxw2fF4PmoSkvmOjPfKyeRQqu/aHU023zKZWP8lGidwEFb9YrOOil50cn6vmxAIN71X6eHOXj1WXmfoec+mrTrLjJH6/NDAN/OO5Oh5d7+GGd11cv0DHHrPM7z7z8JP5ugGvv6PDz4vbfWy8JhDYpakqVJLE377xkBkrsbNTZt6EyDjHeVQUGT78NXxf7NsWauMuvGwOG063E71Oj00a/k/DDrsDtVrNfz7+z4CfzE0xgQ+Efzz6D/715L+45Z5bKC4rxmQy8Yfb/4DXG5im1BuObCm6VrN/Sm1fkMrKoS8u7c9r9uJ3+NFl6pA0R3DNzd5cU7yD/6iceExi0LJ3gNo/1ZK4OJGk45IG3F/2yLT8s4WJ10wMrF6U9597U3zKgCANJ8NrDWXF5/GMaUf5r5v9nLhy/yzCzz5wA25+MEPLM2cbOadMy+NnKPz+Mw8/ec9FSYqKVy40cmzu/n/i9b0yKmn/SDsnQcX73zfx0/fdTP+rnex4iRsW6LjlmODwUhSFq9908cByPTG6wPeXUSvxzNkGrnvHhdsHj55mIDt+HE8Z9lf5IdSsgYLjQ11JVBtX4eX3+7HYLKhVavwq/2FHXQBbv9ka9PvNX28mtzCXsullgUa+HV3MWTRn0MduXL+RE089kTMvOBMIjPrqquqYVBJYIp5XmIfBaGDdmnWcf8n5R/nuBuc1e/HZfejT9UgqCWXv3M2+8PB2eelY1UHs1FjUcWp8XT463u5ApVURNyOu73l237qbzAsyiZ8TjyZWgyY2+FtDUktoEjToswYGcscbHcROj8WYFxhxmopNtL7YStJxSXR93IWp2DTgMeFiOCMvp8OG7Pf1bUSpUnzolcEXBY2UJfkalF8fehHMFbN0XDFr4Khpn1WXDVzavihHw7ofHvpjQJIkPrti4GPPmKztu2A56nx4J1z1CQyxobMwcsZVeNmddjxeDwa9AatkPaLHtDS2cP8d93PBDy6gYksFzz39HL+4+xfkT8rn9PNP55crfslNd91E2bQyus3drFuzjsnlkznhlBPIK8zjgzc/YOP6jcQnxvPsX5/F3GHuCy+9Qc8V11/BA3c/gFanZdb8WXSbu6ncWcl53z9vRN6zzxoIaHdr8PYumqS9f7UasO+20/lBJ7JdRp2gJmZyDIW3F6KJ3//X72n14HcM/To4V6OL3q96Kbq7qO9Y/Nx47DvtVP+uGn2mnok/mjiMdzY2htfXMDCi3zdKNsiiV2bUad4I2/8LU0fm37EwdOMmvPqPunyS74hGXQDfvvDbuFwuvnvKd1GpVXz/6u9zwaUXAHDPI/fwxANP8Kdf/4m2ljaSkpOYPnd63+KKa352DY11jVxz4TUYTAYuuOQCTvrWSdis+6crf/TzH6FWq3nsvsdob20nLSONC39w4Yi9b2O+cdDjsleGLtDGa8n/Wf5hn2fqM1MPeftg57kADBMNTL5vctAxSRVYzHHggo5wNBLdNURD3ii1+o8w5Vwx+goRSem7MGh4XC4XNTU1FBQUYDAMvB5orPRaezH3mDHoDVhUliPqpnHZWZdROrWUW++9dQwqHFuyV6a9sZ37Ku+jxdMS6nLC1kNLHuLkvJOH9JiP//ssX616m9ziwIqzie49HG97YzTKE8Ldd54LdN4Qxty4OMPq8/v6Rl1eyTsu20AJo2M43TUsPebgxRqK2Mcran36QKgriFrjIrxsDhtenxetVjtu20AJo2M404a2A8NLTBtGr6avoXpVqKuIShF/zsvn8wU2mVQPfdT1zOvPjF5hQkQY6oINv9+P3dqLNkxaQwkhpIuDOT+A1MHPBwujK+LDa9+oy6A3YJEsoS5HiCAJ+gR06oMvLR/MvguUtfr953dFeEUXJTYDacE1MPdK0WU+hEYsvI5y3cew+Hw+rHYrGrUGv+QX57r6U0BBQebIL3aONsNdaej1eDDGJvQdM4hpw6jQKyXwhT2XonP+SNGMRaEuJ+oddXhptYGLFB0OR19bpLFidVj7Rl0OxLU2/SkeBZ/so9fXG+pSwtawrvGyWQOtocKkKa8w+jo1mewwzKdRV0R95w6s69YwafrCg/b9FMbGUYeXWq0mMTGR9vZ2AEwm05j8pXp9Xrp7ugHweX24VC4UwrcN0ZhRAsHVbe5mjXkNLnl0Oz9EsmG3hvJ50ez9oU1SZPSKWCQ0HjVrC9hhnEebZiIOay/m+grUWi16Y/h2jIkmIzJtmJmZCdAXYGPB6XJid9jRarX48OGW3Id/UBRQCIy41pjX8FbHW6EuJ6wNZ5m802FHkqT93TUUByrxQ9O4IaOiTlfKDuNcetSpWHvMdHdsR280UTprITMWnUhu8dRR/QG9x+Eh0TS0c7HRaETCS5IksrKySE9P72tKO5rcHjeP/fsxLDYLWWlZfKr7VCzW2EtGptfXK0ZcR2C4I6/+WWUQU4bjghctVYZp7DTMwSbF0tPZhqV7K7HxScw+9hSmzj+eCfnFoxpale02nlxTxWubmnnt2mMonxA5G7qGwoiuNlSr1ajVo78twrbKbeyq2UX+xHwa3A3sknYd/kGCcIDhhJfDbkXp9/klrvGKbC7JyC7DbPYYZuCUtXS1t2C31JKQks4xp57PlLnHkpo5ur05N9R18/jqKj6qaGPfurenP63mgYtmjurrRrqIWyqvKApfbv4SAL1Oz2bN5hBXJESq4SzYsHab0fTbwkYs1ohMVlUiFcY51Oin4PLKmBubcLscpGRks+DkMymftZj45KF/fxwpRVH43852Hl9dxVe13QNuf3NLMzefWkpmQuha7oW7iAuv5vZmtu/eTnpKOl681KnrQl2SEKGGsx2KtbdLrDSMYGZ1BhXGeTToinG5XHTW1uD3+8icWMDMY5Yyefp8TLFxh3+iYfL6ZV7f1MyTa6rY3XbwUbvXr7Dyi1puObV01GqJdBEXXht3bKTH2kN2ZjZV6ip80pF1jxeEAw112lCWZWy93WhFeEWcFm1eYOWgNg+7tRdzw05UKjU5k0qZsegkiqfNRas7ss1jh8Pu9vH8+nr+9lkNLb1Hdj76pa8b+NmyyWjV46KL34iLqPByuV18/s3nxMfGI0kSVZqqUJckRCiTxoRJO7Qlz26nA5/HjaZfayhxgXL4kpGo15WwwziPbnUa1p4uuju2oTcYmTx9HjMWnUT+5GmoNaP3MdhhdfOPtTX8a10dFtfQftDutHn4YHsbp0/PGqXqIltEhdf2yu00tTWRPzGfLqmLLlVXqEsSItSwdlC2W/F6PehN+3cVFh3lw48PDVWGqew0zMUqxdFrbqfXvJWY+ERmLj6ZaQuWkF0weVRXDtZ22nliTTX//aYRt2/4XW6eX18vwusgIia8FEXhy01foigKep2eLZotoS5JiGDDWazR19ew3/SSmDYMHy7JwB7DLHYbZuJQdHS3t2DrrSM+OZXFp5zDlHnHkTYhd1Rr2NzQw+Orq3h/eyvyCFz+t7aqk3qzg9wUcWH0gSImvJrbm9m2exvpqekoKDSoG0JdkhDBht1dw+tBvW+1oaKI67zCgE0Vz07DXKoMU3F5FcxNTbgdNlIyspl34umUzzmGhOSh/30PxapdgZWD66pHdjZIUeCFr+q5WSzcGCBiwqv/Qo1OVafoqCEclWH1NXQEgkqlCpxA1ytO1KLxcch0qdOoMM6jXleCy+XCXFeDz+slY2I+Mxd/j5KZCzDFjt6Fvj6/zFtbWnh8dRU7W62j9jovbWjkZ8smoxELN4JERHgduFCjWdUc6pKECDfcc17922uIUVdotGpyqTDOo0WXj8NmwdywC0mlYmJhSd/KQZ1+9K6Pcnh8vLC+gb99VkNTz+j3teywuvmooo1Tp4pzX/1FRHhtr9xOc1szeRPzAGhSN4W4IiHSDXc7lP47/4jzXWNHRqJBV0yFcR5mdQa23i66areh0xsomjqHGYtOpKB0xqiuHDTb3Kz8vJZn19XR4xj9Nnj9vbqxSYTXASIivHbs2YFP9qHX6bFLdnpVYpsP4egMt7tG/w9HEV6jz4eGGv0UKoxzsUjxWLo66OnchikunukLT2T6wiVkF5T0TeWOhoYuB0+uqealDQ24vKGZJl61qwO720eMPiI+ssdE2P9JuD1utuzaQmJ8IoCYMhRGxHBGXpbeLjTafisNFXGN12hxSwb2GGawyzAbh6Knu6MFW0898UmpLFz2babMPY707LxRXe6+ramXx1dX8e62VvwjsXTwKLh9Mh9VtHHWzOyQ1hFOwj68ahpqMHebmZgVaI7ZrBbhJRy9oZ7zUhQFW0+X6K4xyuyqOHYa5lBlmIbLB+bmZpx2KynpWcw962LKZi8mKTVjVGv4dE8HT6yu5rPKzlF9naF6c3OLCK9+wj68Kusr8Xg9GPQGfPhoU7WFuiQhwunVehL0CUN6jMftwu1yHtBdQ4TXSOlRp7LDOI86XSlut5vOujp8Xg/p2Xkcf/pFlM5aSEzc0P7OhsIvK7y9tYUn11SxrSk8t1das6cDq8tLnEF7+DtHgbAOL0VR2LRjE0ajEYA2VRt+yR/iqoRIN6xl8nuv8TIZ9n+AipHX0WvTTKTCOI9mXSFOuxVz425AIbughBmLT6Z42lz0BuOovb7L6+c/Xzfw9Kc11Hc5Ru11RoLHJ/PhjjbOnT26W7REirAOr+b2ZpramkhOSA78XkwZCiNg2N01PB4xbTgCZCQadUVUGObRqcnEZummu3Y7Wp2egrIZzFx0EgVlM9FoR2+E0ePwsPLzOlZ+UUuX3TNqrzPS3t7SIsJrr7AOr6r6Kqx26/7zXWKxhjAChttdw+v1HLAdiliwMRR+1NToywMrB1VJ9O5bORgTx9T5xzF94YlMnFQ2qisHG7sdPP1pDf/5ugGHJ/JmcT7d04nN7SNWrDoM7/DaXrkdtUaNJEl0S904VOE9rBciw/CmDW0oioxq707hWtmNBrEdz5HwSHr26Gewyzgbh2Kgu7MVS3cj8UkpzD/xDKbOP46MiQWjunKwosXCE6ureGtLC74Qrxw8Gh6/zOeVnZwyJTPUpYRc2IaXxWZhZ9VOkuKTADFlKIyc4XXXsNH/o1Uskz88hyqWnYbZVBpm4PJJdLU047D2kpSWyQlnfpfy2YtJTh/dC28/r+rk8dXVrNndMaqvM5ZW7+6IqPB65plnuPHGG+np6RnR5w3b8Kqqr6K7t5tJeZMAxCpDYcQMu7tGv9+LlYYH16tOpsIwj1p9GS6Pl876enweF2lZeRz7rfMpnbmQ2ISkUXt9WVZ4b3srT6yuYnPj+GtosGbP+AnioxG24bW7ZjeyLKPVaFFQxN5dwogZzrShrbcblUrd93uxWGOgds0EKozzaNJOwumwY67eg6IoZOUVMeuYpUyePg+9cfS29nB5/bzyTSNPramm1jx+TzE0dDmp6bRTkBpz+DuPY2HZptjr9bJ552bi4wIdoS2SBa80tr3EhPFrONOG1h5z0DVeIrwCFKBRO4kP4r/Dh/HfYZcrhfrKCro7WsgvmcbZV9zId1fcwbQFJ4xacPU6vTz2SSXH3vcJv3p127gOrn1Gahr0vffe49hjjyUxMZGUlBTOOOMMqqoCO9TX1tYiSRIvvPACixcvxmAwMHXqVFavXt33+FWrViFJEm+//TbTp0/HYDCwcOFCtm3bdsjXff3115k9ezYGg4HCwkLuuusufL6hnUMOy5FXXXMd7eZ2MtMC87pmlTnEFQnjyXBGXpYB3TWi+5yXHzW1+lIqDPPoVSf39Rw0mGIpn3MM0xcuIbd4yqiuHGzpdfK3T2t4fn099ghcOXg01uzu4AeL84/6eex2Oz/72c+YPn06NpuNO++8k3POOYdNmzb13ecXv/gFDz30EOXl5TzwwAOceeaZ1NTUkJKSEnSfhx9+mMzMTH75y19y5plnsnv3brSDXO7w6aefcumll/LII49w3HHHUVVVxdVXXw3Ar3/96yOuPSzDq76lHpfbhXHvxYkivISRopbUJBuSh/QYr8eNy2E7YJl8dI68PJKOSv10dhlmY8dET2cblu6txCYmM+eEbzF1/vFk5U4a1ZWDu9usPLG6mjc2N+H1R+7KwaPxRbUZj09Gpzm6Hw7OO++8oN///e9/Jy0tjR07dhAbGwvAihUr+u7317/+lffee4+//e1v3HzzzX2P+/Wvf82yZcsAWLlyJRMnTuTVV1/lwgsvHPCad911F7feeis/+MEPACgsLOS3v/0tN998c+SHV0NLAyqVqu8fgAgvYaSkGFJQSUP7B++02/B5PRhi4vqORduCDacUwy7jLPboZ+KUVXS1NuOw1pCYlsFxp19E+ZzFpGSMbt+99TVdPL66ik92tQdtTRONHB4/mxp6mF8wtB/EDrRnzx7uvPNOvvzySzo7O5HlQNf8+vp6ysvLAVi0aFHf/TUaDXPnzqWioiLoefrfJzk5mZKSkgH32Wfz5s2sXbuWe++9t++Y3+/H5XLhcDgwmY5sejnswkuWZfbU7iHGFDgZqaCgQoVKUSFLYtda4eikmobfGipo2lCJjvCyqJKoMM6lRl+Oy+PD3NCIx+0kLSuHY5afS+msRcQlHt0H6KEoisIHO9p4YnUV39T3jNrrRKKv67qOOrzOPPNM8vLyeOqpp5gwYQKyLDN16lQ8ntHrOmKz2bjrrrs499xzB9xmMBz5JqJhF16d3Z109XYRFxv4KVdC4hT3KcjI9Eg9dKu66VJ10a3qpkfqEb0OhSEZ7jJ5r9cTVQs2OjVZ7DDMo1FXhMvpoLOmCkX2k5U7iRmLAysHjTGxo/b6Hp/MqxsbeWJNNdUd4/vPerg21HYf1ePNZjO7du3iqaee4rjjjgPgs88+G3C/devWcfzxxwPg8/nYsGEDK1asGHCf3NxcALq7u9m9ezdlZWWDvu7s2bPZtWsXRUVFR1V/2IVXc3szNruNrLTgixdVqEhWkkn2JzPJH7j2S0bGIlnoUnUFAk3qplvVLQJNOKjhNuWV/f6+pfJqxYtOcY90aSGnAM3aAnYY59OuycZh7cVcX4FaoyG3qJyZi09i0pTZaHX6wz7XcFlcXv69rp5/rK2h3Tr+/oxH0jf13SiKMuzzi0lJSaSkpPDkk0+SlZVFfX09t95664D7PfbYYxQXF1NWVsaDDz5Id3c3V1xxRdB97r77blJSUsjIyOBXv/oVqampnH322YO+7p133skZZ5xBbm4u559/PiqVis2bN7Nt2zbuueeeI64/7MKrpb0FWZZRq9WHva8KFYlKIon+RAr9hUBgmnFfoHWruumSAr/6JNHKRxhmdw2HHUmS+j4kxtv5Lj8q6nWl7DDOo0edgqW7k56ObehNMZTOWsiMRSeSWzz1iP5NDlebxcXfP6vhuS/rsbrFv9Uj0e3wUtNppzBteCNglUrFCy+8wE9+8hOmTp1KSUkJjzzyCEuWLAm63x/+8Af+8Ic/sGnTJoqKinjjjTdITU0dcJ8bbriBPXv2MHPmTN588010/WYq+lu+fDlvvfUWd999N/fddx9arZbS0lJ++MMfDqn+sAuv5vZmnG4nlXWVxJpiiTXFYjKajnjJrYREgpJAgj+BAn8BEAg0q2TtG53tCzZx7Vj0GW5TXqXfCoHxMmXoRUuVYTo7DbOxSbGBlYNdW4lNSGL2ccuZtuAEsvKKRnXlYGW7jSfXVPHaxmY8fnFOe6g2N/YMO7wAli5dyo4dO4KO7fter62tBaCsrIwvv/zykM9z7LHHHvTarssuu4zLLrss6Njy5ctZvnz58IreK+zCa/lxy0lPSae6oZqGlgY6uztxtAQuOtRqtMTGBAItxhgzpECLV+KJ98eTTz4QCDSbZBsQaB4pcrZHEIZuONOGDqsFqd/3WqSHl1Mysdswi92GmbhkDV1tzdgttSSmZnDMt85nytxjSc0c3W03NtR18/jqKj6qaIv6lYNHY3NDL+fMis4tUsIuvCZmTmTi3n84Hq+HdnM7rZ2ttHa0UttYS11zHV09XTS2NKIoChqthjhTHDGmGGKMMUc8tSEhEafEEeePI4+8vuM2ydYXZvsCzS2JuffxYjgjL0t3x7jYCsWqSqTCOJdq/RTcXj/mxibcLgcpGdksXHoWZbMWEZ889HA/Uoqi8HFFO0+sqeKro1xsIARsaugJdQkhE3bh1Z9OqwsKMwi0jmrvCgRaW0cbtU211DTV0GPpoam1KRBoGk1gdGaKIdYUO6S5+lglllgllhw5p++YXbIHjc66VF24JNeIvldhbAyrNVRvd0QvkzerM9hhnEeDbjIulwNzbTV+v4/MnAJmLl7K5OnzMcXGHf6Jhsnrl3ltYxNPfVrN7rbIDP5wtbPVgiwrqFQjP7Wbn58fNF0+mCVLlhz2PqMlrMNrMFqtluyMbLL7XRDp8/no6OroG6HVNddR01iDxWqhub0ZRVFQq9SBc2gxgVDTqI/8rccoMcQoMUyU94eoA0fQsv0uVRdOyTmi71UYWRISKcaUw9+xH7/Ph8NmCRp5RcqCjWZtPhXGebRpc7FbezE3VKBSqcmZVMrMxSdTNHXOqK4ctLl9PP9lPX9fW0NLr/hhbzS4vDKN3U5yU0av4XG4irjwGoxGoyErPYusfnsD+f1+Ors7aeloobWzlYbmBqobqum19tLS0YJf9u8PtL1fGs2R/3GYMGGSTWTL+0PUiTM40KQusYFmGEnUJ6JVDW1reacj0F1Dt7dVGYT3OS8ZFfW6yewwzqNbnYa1x0x3xzb0BhOTp89nxqITyZ88DfUQvteHqsPq5h9ra/jXujosLrFycLTtabeK8BpP1Go1GakZZKRm9B2TZZnO7s6+EVpDSwNVDVX0WHpo7WhFVmRUKhUxxhjiYgLn0bSaI/+wM2LEKBuZIE/oO+bCNSDQ7Krw/fAbz4bdXcPjISYuoe9YOIaXDw1VhmnsNMzBKsXRa26n17yVmPhEZi4+mWkLlpBdMHlUVw7WdNp5ck01r3zTiMd39CsHfdZOelY9g7N6A4rPjSYxi5TTbkSfVXzQx1i/eQvLhrfwW9pRx6eRsOhCYqee3He7s2YjXR/+Fb+9G1PxQlK+9RMkdeDfuOy207Lyp2RcdA+ahPSjrn+s7Gm3cXJZxuHvOM6M2/AajEqlIj0lnfSUdKaXTAcCgdbV00VrZystHS00tjb2bYTZ1tmG3+9HUkl9o7MYUww67eDXLwzGgIEsOYssef+o0I17f6DtPZdmk2wwep8rAkfZXUO7f3otnBZsuCQjuw0z2W2YhVPR0t3egq23joTkNBafcg5T5h1H2oTcUa1hc0MPj6+u4v3trcgjdPrD77LR+q+bMeROJ/2C36AyJeDrbkZlOPiycOvGd+hevZKUU69HlzUZT/MuzO8/isoQi6loAYoi0/nmH0lYeAGGgtl0vPZ7rJveI37OmQB0r3qGuJnfiqjgAtgTpecRoyq8BqNSqUhNTiU1OZWpk6cCgVVR+wKttbOVptYmKusr6erpoqOrA5/fhyRJxBhj+s6jDSXQ9OjJlDPJlPdv5e3BMyDQrJJVBNoIGm53Db/P2zfNJil+9Eroz23aVAnsNMyhyjAVl1fB3NSE22EjJSOb+SedQdnsxSQkDz2sh+KTXe08sbqKddUjv1GsZd3LaOJTST39xr5j2sTMgz8AsG/7H3Ezv0VM2fF993e37sGy7hVMRQuQHRZkp4W42acjaXSYihfgNTcC4GqswNO6h+RlPxrx9zLaKjtEeAl7SZJESlIKKUkpTCmeAgQCrdsSGI21dLTQ1NpEVUMVnd2dmLvNeP1eJCRMJlPfKE2n1R3xNI0OHRlyBhny/uG/F29Ql5B9gaZI4sKY4RjeBcoHdtdwhPTniS51GhXGedTrSnC5XJjravB5vWTmFDBj0fcombkAU2z8qL2+zy/z5pZmnlhdzc5W66i9jrPyy77RkathG+rYFOJmnUbczFMP+hjF7+2bAtxH0uhxt+xG8ftQmRJQxybjrNmIIX8G7obtxEw7GcXvo+uDx0g57UYk1eh1ERktVe0ivIRDkCSJ5IRkkhOSKZsUaDipKAq9tl5a2wMjtOa2ZirrK+no6qChpwGP14MkSRiNxr5A0+v0RxxoWrSky+mkkw572zX68NGt6g66Fs0iWUSgHYFhtYayWwNN//YK1TL5Vm0uOwzzaNXl47BZMDfsQlKpmFhYwsxFJ1E0bS46/ZF35B4qh8fHC+sb+NtnNTT1jP7I09vTinfjO8TPO5uMRRfibtlD98dPIqm1xE47edDHGApmY9vyAcbJi9BlTMLTWolty/sg+/A7LWhik0k96xa6P36aro+fxFg4l9hpy+hd9xKG3OlIai2t//oFfqeFuNln9E0nhjub20dzj5MJicbD33kcEeF1FCRJIjEukcS4REonlQKBQLPYLLR1tgWmHNuaqK6vps3cRmNrIx5voIOHyWDq6xYylEDToCFNTiONtKBA699xf1+giS1kgg23NVT/odZYnu+SkWjQFbPDOJ8udTq23i66areh0xspmjqHGYtOpKB0xqiuHDTb3Kz8vJZn19XR4xjDdmqKgj6ziKQTAhsW6jIm4e2sw7rpnYOGV8Li7+C3d9P6z5+DoqCOSSR26slYvnxl/8h54hSyfvBg32O8XU3Yt/+PrMseoe25W4mb822MhXNo/vt1GHKmoksvGP33OgLquxwivISjI0kSCXEJJMQlMLlgct9xq93at8qxpb2FqvqqvvNpHq8HBQWjYf8IzaA3DCnQUpVUUv2pfYHmxz/oFjLRHGjDGXlZujtR91txOhYrDX1oqNZPYadxLhYpHktXBz2d2zDFxTN94YlMX7iE7IKSI26PNhz1ZgdPfVrNSxsacHnH/ntGHZuENjV4oYk2JQfHrrUHfYxKqyf1tBtJWb4Cv70HdWwSts3vI+mMqEwJgz7G/P6jJJ34Q1AUPG1VmEqPQaU1YMiZiqthW8SEV5sl+q6jE+E1RuJi4oiLiaM4b/8yX5vDRmtHa995tKr6KlraW2hub8btdoMEBr2hL9CMBuMRB5oaNSlKCin+lL5Ai/Y90YazYMPa0xV0Ie9ohpdbMrDHMJNdhlk4FD3dHS3YeuqJT0pl4bJvM2XucaRn543qcvdtTb38dXUV721rxT9SSweHQZ9djrerMeiYt6sJTfzhVwJKag2a+MDftb1iDcZJ85EG2T3buvkD1IY4TMUL8Lv2jqjlwL8FRfaDHDk/6EXjReAivEIo1hRLUV4RRXn7N2WzO+2BKceOwNL9moYaGtsaae1sxeV2gRIItJiYwEpHk8F0xB9mh9sTrf/ikPEYaEOdNpRlGbu1Z9T7GtpVcew0zKXSMA23T8Hc3IzTbiUlPYu5Z11M2ezFJKWO7nU8n+7p4PHVVaytNI/q6xyp+Hln0fqvX9D7xX8wlR6Lp2U3ts3vkbx8/yaI3aufwW81k3rGz4FAuLlbdqPPmozssmH56jW8HXWknv7TAc/vt/fQ+8WLZF58PwBqQyzalBwsX72OsWAWrrrNJCy6cGze7AhoFeElhFqMMYbCnEIKcwr7jjldzkAvx70jtOqGahpbG2k3t+N0OkECvU5PjCmGOFMcRoPxiKeU+u+Jtm+ENh73RIvTxmHQDG1Bg8thx+t2oxmlkVe3OpUK4zzqdKW43G7MdbX4vB7Ss/M4/vSLKJ21MOji6JHmlxXe3trCE6ur2N5sGbXXGQ591mTSzvkVPatX0rP2eTQJGSSddBWxU07su4/f1o3P0rH/QbKMZf2r+LqaQKXGkDedzO//EU3CwODv+vhJ4uedjSZuf7uwlNNupPPtB7FueJP4+eeiz5o84HHhqqU39JdvjDVJCVVXReGouNwu2syBEVprRyvVjdU0tjRitVtxuAItqXRa3bD2RBtMpO+JVpBQwBtnvzGkx5jbmvnnA7cTl5iCcW/j2uU9/yLF33ZUtbRpJrLDOJ8WXQFOmxVzayNIkF1QwozFJ1M8bS56w+idfHd5/fzn6wae+rSahq7o+9Abj2ZMTOD1FceGuowxJUZeEcqgN5A3IY+8Cfu3c3F73LSb22npaKGts42axhrqm+sx95hpaGlAQRmVPdH2jc7CeU+0o+quoes/bTi8kZeMRKOuiArDPDo1mdgs3XTXbker01NQPpOZi06ioGwmGu3Qei8ORbfdw8ovann2izq67OH3dyQMnzjnJUQ0vU5PTlYOOVn7t3PpvydaW0cg0EZjT7Rc9q8MC8c90YbbXcPn9ew/56UoGIZ4nZcf9f6Vg6pEes3tgZWDsXFMnX880xcuYeKkslFdOdjY7eDpT2v4z9cNODzj71ymAJ02Nz6/jEY9et9H4UaE1zh3sD3ROro7AiO0jra+LWR6LD00tzUjy/K42xNteNd4BRZn9F0jpDhQcWSz7B5Jzx7DDHYZZuNQDHR3tmLtbiAuKYX5J53B1PnHkzExf1RXDla0WHh8dRVvb2nBF8KVg8LokxXodXpJiR29LW7CjQivKKTVapmQPoEJ6fu73wftidbZSn1zPTWNNfRae8fFnmjDucbL5bDRP1uOZB8vuyqWXYY5VBqm4/JJmJubcNosJKVlcvyZ32XKnGNISjt0j76j9XllJ4+vqWbN7o7D31kYN+xuPykH71s87ojwEoBD74m2r+P+gXuiyXJgC5lI2BNtONOGDpuF/suZDnW+q0edQoVhLrX6MtweL5319fg8LtKy8jjutAsonbmQ2ISk4ZR+RGRZ4b3trTyxuorNjb2j9jpC+LK6I2Px1EgR4SUcVP890WaUzgAC1z6Ze8yBTT47WmlsbaSyvpJeS29gCxnZP+J7orlxB50/G86eaMOZNrT2dh/QXWPgNV7tmmwqjPNo0hbidNgxV+9BURQm5Bczc/HJTJ4+D71x9DYKdHn9vPJNI0+tqabWLDY+jWa2KNv4M+LDq+MvjwJgmDIFw5QpaDMiay+eSKNSqUhLTiMtOW3QPdFaOwObfFY3VNPV09UXaJI0/D3R9OgH7InmwbM/0I5gT7ThbERp7e5EO8hKQwVo1E6iwjiPDs0E7NYeuuoq0Gi15JdMY8bikygsmxX02JHW6/Dyz3W1PPN5HZ220C6GEcKDzS3CK6J0v/ACfvP+rgDqtFQM5eUYyssxTpmCobwc7YQJh3gG4WgddE+03q7AdWijsCeaDt1B90RrcDVg0VowZBhosDUgK/KQR16KomCzdAdtQqlTXFTpp1JhnEuvKrmv56DBFEv5nGOYvnAJucVTRnXlYEuvk6c/reGF9fXYxcpBoR8RXhHE294eFFwA/o5O7KvXYF+9pu+YOjkZQ1lZYHRWXo5h6hR0Eyce+HTCCJIkiZTEFFISB98TrbUj0HG/sr4Sc7c5eE804/6O+8PZE83X5aM0vpR7z7kXh8/Brq5dxOnihlS/2+nA43YFXXe1yXQcfhl6OtuwdG8lNjGZOSd8i2kLTiAzp3BUVw7ubrPy+Ooq3tzcjNcvVg4KA1nFtGH4UhSFjqYm4pKSMMbE4K6oOKLH+bu6sK9di33t/o7U6oQE9OVlfaMzw5QpaHNzR/UDKNodak+0to5A66vmtmaqGqpoN7cH9kTzeZAY2p5oHp+H5PjkwMhOG8PsjNlDrtXpsOHzeokxxgDg83npamvGYe0lMS2T406/iPI5x5CSMbqj+i+rzTyxpppPdrUjeuEIh2IXI6/wtfXzz3n3X/9Cq9ORkpVFSXMzw+385u/txfHFOhxfrOs7poqLCx6hTZmCrmB0r8WJdv33RCspLAECgWa1W/umHJvbm6mqqzriPdE8Hg/JiclHVZfTbsXrcaMoCi11VXjcTtKycjjm1PMonbmQuKN8/kNRFIX3t7fxxJoqNtb3jNrrCOOLxxc5XfBHQkSFV2tDA7aeHpIzM2mqqiKlYueww2swstWKY/16HOvX9x1TxcSgLyvdfw5tyhR0hYVIo3heI9pJkkR8bDzxsfGD7onW1tEWCLSGqsD0Y2sTbk9gCxmjwYjT5STpKJelu/aOvLpam8jKL2LGopMpmTEfgynmaN/eQXl8Mv/9ppEnP62muiM0OzYLkSvarkOPqPBqrq7GFBdHUloaSWlppO3eM+qvKdvtOL/egPPrDXTvPSYZjRhKS/tGZ4Yp5egnTUIaxR1thSPbE626oZq2zragFlnDkZqZw+zjlpFbPIVJ5bNHdeWgxeXl3+vq+cfaGtqtYuWgMDxylM0rR8ynrdNup6utDUPM/p989VZrSGpRnE6cGzfi3Lix75ik16MvKcEwZf9KR31xMdIoNloVBt8TzeP1DGnl4mDik1I45YIrj7a8Q/L4ZF7b2MS/19djcXhQKz4S1F483sDFphqNBpVKTFkLA/n3ThGmpSb1TZcnmqLrsyZiwqu3sxOn3U5KZmBptOTzoXOEz0WZituNa8sWXFu29B2TdDr0xcVB59D0JZNRjeJP8QJHHVxjRadRcUpJIonORj75fCt1rc3otFqys9IxGoa295gQXTq7uvH5/PxxxU+j9nslcsKrqwuPy4Vu71+UwWo92PWoYUPxeHBt345r+/b9B7Va9EVFwSO00lJU+uhpqClAW6eZL77ezOovN9DS1klsrImiglx0YqQuHJHAp58cbSe6+omY8LJ2B8447bsA1GAJzZThUfN6cVdU4K6ooJdXAsc0GvSFhf3OoU3BUFaKyjh6GxIKY09RFOqbWvjsq418/vVmzN09JCUmUFZcMKSu/YIgSYH99KJ5L+GICa/eAy5GNoTofNeo8Plw796Ne/duel97LXBMpUJXWBDUKURfVo46dvRWuwmj671P1vLGR6tpbm3H6/MTHxdDr8VKb6T+ICaEjNfnIyM1RYRXJOhsbg5a8aV1hs/5rlEhy3gqq/BUVmF5483AMUlCl5cXdA7NMKUcddzQukcIoZGfM4Hlxy8KdRnCOJGWkkRszOg1fQ53ERFeiqLQ2dqKvt80ms45Ovs+hTVFwVNbi6e2FsvbbweOSRLanJygc2iG8nLUiYkhLVUYqKy4kLLiwlCXIQjjQkSEl91iwWm19i3WANA6x24X3rCmKHjr6/HW12N9972+w9rs7OAR2tQpaJJGbz8pQRCEsRQR4WXt7sbtchHbbzShdYnwOhRvUxPepiasH3zQd0yTlbU3zPZ3C9GkDn2rEEEQhFCLiPCyW6143W50/ZaTa6Jx2vAo+VpasLW0YPv4475jmvT0oPNngT3RMkJYpSAIwuFFRHi57HYURUG1dzmx5Pej8XhCXNX44Gtvx9bejm3Vqr5j6tRUDOVlfaFmnDJF7IkmCEJYiYjwctqDm5RqXa6wv0A5kvk7O7Gv+RT7mk/7jqmTkvo2+dw3StPlHF3/QEEQhOGKiPBy2e3038xI4xbNS8eav7t7wJ5oqoSEvhFa367VeXliCxlBEEZdRISX3WIJ2oJE5Y2uTdfClXywPdFKS/d3CplSji4/X2whIwjCiIqI8LJ0dwdtx67yi/AKV7LViuOrr3B89VXfMZXJhL6sLOhaNF1hIZJoiSQIwjBFRHjZenvR9Ouuofb5Q1iNMFSyw4FzwwacGzb0HZOMRgwlJUHXoYk90QRBOFJh/0mhKEogvPp9qImRV+RTnE6cmzbh3LSp71jfnmjlZfsvsJ48WeyJJgjCAGEfXrLfj9/nQ9U/vHwivMajQfdE02rRT54cvGt1SYnYE00QolzYh5fP60WR5b5rvABUYtowaihe7/490V56KXBQq0U/aVLfRdXG8vLAnmhRuimfIESjiAgv2e8XCzaE/bxe3Dt34t65k95X/hs4plYH9kTbN904dQqG0lJUpujtui0I41lkhJcs921CCSBF8R42wkH4/bj37MG9Z0/wnmgFBcG7Vos90QRhXAj78PL7fMiyHLSsWhEXwQpHQpbxVFXhqRpkT7T+nULEsn1hBKkTEsSq2TEQ9n/C+6YN+4+8RHgJw9Z/T7R33gl1NcI4VPDfVzCUl4e6jHEv7NseDDZtiBT2ZQuCEK1EN5kxEfZ/yrLfj6IoQe2FxMhLEISwJX64HhNh/6csqVSBDvL9FmkoKhFegiCEJ0l8Po2JsA8vlUqFJEko/cNLjLwEQQhTktEY6hKiQtiHl6RSwYHhJeaUBUEIU6oYcSnGWAj7FJAkacD+ULJG9LoTBCE8qUV4jYmwDy/VICMvn+hrJwhCGJJ0OiTx+TQmwj68pL3nvPov2PDpxTeHIAjhR0wZjp2wD6/BFmz4xU82giCEIRFeYyfsw0ut0aBSqZD9+zvJi2lDQRDCkSo2NtQlRI2wDy+90Yhao8HXbw8vv06HaM0rCEK4UYvwGjNhH146gwGNRoO//waUkoRf7K4rCEKY0aSnhbqEqBH24aVSqdAbjcHhBfj0+hBVJAiCMDhNekaoS4gaYR9eAMbY2AHh5REnRgVBCDOaDBFeYyViw8stwksQhDCjzUgPdQlRIyLCyxQXN8jIS2zvLghCeBEjr7ETGeEVG4ssy0HHxMhLEIRwI8Jr7ERGeMXFDTgmznkJghBuNOli2nCsRER4xSYkgKIEddkQ4SUIQjhRp6WiEg0UxkxEhFdMQgKqA671EtOGgiCEE31BYahLiCoREV6x8fHo9Hq8bnffMVmrxSM2fRMEIUzoJonwGksREV4x8fFo9Xo8/cILwJmQEKKKBEEQgomR19iKiPAyxsZiMJkGhJcjKTE0BQmCIBxAVyjCayxFRHhJkkRCSkrQtCGAMzExNAUJgiAcQC+mDcdURIQXQGpWFh6XK+iYCC9BEMKBymRCk5kZ6jKiSsSEV0pmJrISvBGKIzFRbI0iCELI6QoKAju+C2MmYsIrMS0NCYI2pZS1WnG9lyAIIWcoLw91CVEnYsIrKS0Ng8mEy+kMOi4WbQiCEGqG6dNCXULUiZjwSkhNxRATg8tuDzpuT0kJUUWCIAgBxukzQl1C1ImY8NLp9aRkZuJyOIKO21LFzqWCIISOymRCX1wU6jKiTsSEF0Bmbi7uA1Yc2lJTxKINQRBCxlBejqSKqI/ScSGi/sSTMzKCmvMC+PV6XAnxIapIEIRoZ5g+PdQlRKWICq+UrCw0ajVejyfouDVNbEMgCEJoGMVijZCIqPBKy8rCFB+Pw2oNOm4Ve+gIghAixlmzQl1CVIqo8IpJSCA5I2OQ8BKLNgRBGHu6wkK0YvfkkIio8JIkidzJkwesOHTHx+M2mUJUlSAI0Spm0aJQlxC1Iiq8ILDiUFEUZFkOOt47IStEFQmCEK1iFovwCpWIC6+MnByMsbE4D7hYuXdCdogqEgQhKqnVmBYsCHUVUSviwis5M5P4pCTsvb1Bx3snZKGIxpiCIIwR47RpqGNjQ11G1Iq48FKr1eSXlg5YtOHX6bClpoaoKkEQoo2YMgytiAsvgNzJk1FkecB5r57sCSGqSBCEaBOzeHGoS4hqERle2ZMmYYqPx26xBB3vnSDCSxCE0adOShLXd4VYRIZXUno66RMnYu3uDjpuT0nBazCEqCpBEKJF3NKTkdTqUJcR1SIyvCRJonj69AHXeyFJdOXmhKYoQRCiRtwpp4S6hKgXkeEFgalDjUaD1+0OOt6Vnx+aggRBiAqquDhiFi4MdRlRL2LDKys/n/iUFCwHTB1aMjLwGI0hqkoQhPEu9sQlSFptqMuIehEbXgaTifyyMqw9PcE3SBJdubkhqUkQhPEvXkwZhoWIDS+AwvJyFFnG7/cHHe/KzwtRRYIgjGeSyUTMsceGugyBCA+vgvJy4pKSsHR1BR23pqfjEY16BUEYYXEnn4xKrGgOCxEdXnFJSRROmUKv2Rx8gyRhzhNTh4IgjKzE884NdQnCXhEdXgDFM2YEpg59vqDjnZMmhagiQRDGI+3EiaIRbxiJ+PAqKCsjPjmZ3gOmDh3JydhSUkJUlSAI403COWcjiebfYSPiwys2MZGiadOwHDh1CLQXF4egIkEQxh2VisRzzgl1FUI/ER9esHfqEAZMHZoL8vFrNKEpShCEcSNm4QK0ondqWBkX4ZVfVkZSWhrd7e1Bx2WtFnNBfmiKEgRh3Eg497xQlyAcYFyElykujikLFmDp6kJRlKDb2osnh6gqQRDGA3VSEnHLloa6DOEA4yK8AEpnz0ZvMuG02YKO21NTsCcnh6gqQRAiXeKFF6LS60NdhnCAcRNe2ZMmkVNcjLm1dcBtbSUlIahIEISIp9GQ9L3vhroKYRDjJrxUKhXTFy/G5/EMvOarsEA06xUEYcjiTzkFbUZGqMsQBjFuwgugaPp0EtPT6enoCDquqNW0lpWGqCpBECJV8uWXh7oE4SDGVXjFJiQwZf78ARcsA7RPnoxfbGMgCMIRMs2di3Ha1FCXIRzEuAovgLK5czGYTNgtlqDjfp1OXLQsCMIRS77iilCXIBzCuAuviUVFTJo6lY7m5gG3tZaVIqvG3VsWBGGE6YuLiD1xSajLEA5h3H2SS5LErBNOQKVS4XI4gm7zxMRgzs8PTWGCIESM1OuuE30Mw9y4Cy+ASVOnkjt5Mp2DjL6ap01FEd+UgiAchL6khLjly0NdhnAY4zK81BoNc5Yswev14vV4gm5zJSTQWVgYosoEQQh3qSvEqCsSjMvwAiiZPZusvLxBR1+NM6aLc1+CIAygLy8jbqloBRUJxu0nuM5gYPaSJThttgEXLXtiY2mfLFYeCoIQLG3FCjHqihDjNrwApsyfT1p29qArD5umTRPbpQiC0McwdSpxJ50U6jKEIzSuwysmPp75y5bhsFjweb1Bt/mMRlpLRdcNQRAC0n56Y6hLEIZgXIcXwPTFi8nKz6e9sXHAbS1Tp+DT6UJQlSAI4ST2xBOJPeaYUJchDMG4Dy9jbCzzTzkFt9M5YOWhX6ejccb0EFUmCEJY0GrJuOXmUFchDNG4Dy+AqQsWMLGoiLb6+gG3tZWU4EhMHPuiBEEIC8mXXIJONC+IOFERXnqjkQXLluHz+fC4XME3qlTUzp8XmsIEQQgpVXIyqdf+ONRlCMMQFeEFUDZvHnmlpbQOMvqyZmZizs8LQVWCIIRS+o03oI6NDXUZwjBETXhpdToWLV+OJEnYrdYBt9fPmSOWzgtCFNGXlpJ4/vmhLkMYpqgJL4DJs2ZRPn8+bXV1KIoSdJsnJoZmsXePIEQHlYqsu+9CEp12IlZU/c2pVCqOPeMM4pKT6WprG3B7S3k5zvj4EFQmCMJYSrrkEozTxUrjSBZV4QWQkZPD/KVL6TWbB1y4rKjVVC9eJLrOC8I4ps7KIv3GG0JdhnCUoi68AOadfDITCgoGXbxhS08XnTcEYRzLvvceVEZjqMsQjlJUhpcpLo5jzzgDv8+H024fcHvDrJk44+JCUJkgCKMp9tvfJmbx4lCXIYyAqAwvCCydL509m5ba2gGLNxSNhurFi8X0oSCMJ4mJTPjVL0NdhTBConZtuFqt5oRzzqGhspLO5mbSsrODbrdlpNNaWkJWxc4QVRidHu3s4P/M5qBjBTodbxcENhD9dWsr6xx22n0+TCoVM41Gfp6aRqFef9Dn/NBq5cWebra7XPTKMq/k5VNmMATd5772Nl7t7cWkUvHTtDTOjE/ou+09q4U3env5v4k5I/hOhbGW/du7USckHP6OQkSI2vACyMzN5bgzz+SdZ58lLikJg8kUdHvDrFkkNjZhHOS6MGH0FOl0/C0nt+/3/b9JpxgMnBkfT5ZWQ69f5rHOTn7Y2MCHhZNQH2Sk7JRlZhtNnBoXz51trQNu/8Rm5S2LhadzcqjzeLm9tYVjTTEkaTRY/X4e7ugIqkeIPDHnnEP8smWhLkMYQVE7bbjP7CVLKJk1i+aamkGnD6uOPQZZTB+OKbUkkabR9H0l9bt4/MLEROaaTGRrdZQbDPwkNZVWn4+mA1aO9vfthASuTU1lUYxp0Nur3R7mm0xMNRg5PT6eWJWKxr3P96eODr6TmMQErXZk36QwdrKzmfjrO0NdhTDCoj68tDodJ51/PvHJyXQOsmmlPS2Nxlkzx76wKFbv8XBCZSWnVFfxi+Zmmg8STA5Z5lVLLxO1WjKPIlxKDHq2uVz0+v1sd7lwKQq5Oh0bHA4q3C6+n5Q07OcWQktWq8l/7FFUB0wTC5Ev6sMLIDMvj2PPOANbby9up3PA7S1TptCblRWCyqLPdIORe7OyeHLiRO7MyKDJ6+WS+jrssr/vPs93dzNn9y7m7tnNp3Y7T0/MQXcUo+NjY2I5Mz6eC+tq+WVLC7/PzMKoUnF3Wxu/zsjkhZ4eTquu5uK6Ova43SPxNoUxknj9Cozi0pdxSVIOnCuLUl6Ph5f+8hd2ffMN+eXlSAd8GGqcTqa99Ta6QcJNGD0Wv5+l1VXckpbOeXu3rrH6/Zj9fjp9Pv7R1UWbz8u/c/PQH6bVT5PXw7Lq6kEXbBzosc5OrLKfc+IT+GFjA6/nF7DKbuO57m5ezi8YqbcnjKZZMyl7/vlQVyGMEjHy2mvf9GFCWhptDQ0DbvcZjVQed6xYPj/G4tVq8nU66rz7NxKN23tsrsnEg9nZ1Hg8fGSzjdhrVrvdvGnp5frUNNY7Hcw1mUjWaDg1Lp4dbnfQKFAIT764OIoeeyzUZQijSIRXP5l5eSw55xzcLhd2i2XA7dbMTBpnzAhBZdHLLsvUezykHazjv6KgAB5FHpHXUxSF37S1ckt6OjEqFbICvr2TE/t+9Yu5irAmq1TkPvYo2uTkUJcijCIRXgeYedxxzDruOFrq6gb0PgRonjaV7okTQ1BZdLi/vZ2vHA6avB42Oh38pKkRtSRxelw8DR4PT5rNbHe5aPZ62eh08NPmZvSSxPEx+/dkOr2mmo/6Xd7Q4/dT4XJR6Q6M3mo9HipcLjp8vgGv/3JvL8lqDSfGBjqszDIa+dLhYLPTycruLibpdMSr1aP8pyAcjZgbbyBh/vxQlyGMsqi+zmswKpWKk847j7aGBhqrqsgrKQk+/yVJVB53LFPefQ9TT0/I6hyv2nxebmpupkf2k6xWM9to5PncPJI1Gnw+LxucDv7Z3UWv30+qRsMco4nn8vJI6Tcyq/F4sPab2vvEZuVXrfuv7/p5S2BV6bUpKaxITes73unz8YS5k+fy9m9MOt1o5LKkZH7U2ECKRsPvMsXCnXDmXXICZVdfHeoyhDEgFmwcRP3u3bz48MMoikL6ICMtnc3G1LffQStWnwlCWHBMnMiMt99Cc4huK8L4IaYNDyJ38mSWnHsuDptt0PNfnthY9iw5AVlsZicIIecymZj05BMiuKKI+OQ9hNlLljBnyRJa6+rwDDLCsmZkULtAzK0LQij51GpS77uPxMLCUJcijCERXoegVqtZeuGFTJ41i8Y9e5D9A5dIdxQXi/2/BCFEZElCdcMN5CxbGupShDEmwuswjLGxnHbppWTm5dFQWTmg/yFA3dw5dOWIjuOCMNZs551H+VU/DHUZQgiI8DoCKZmZnPaDH2CKixv0AmZUKiqPPw5LRsbYFycIUap98SLm/PrOAd1whOggwusI5ZeWsuw738Hr8dDT2TngdkWtZveJS7CLCyMFYdS1Ti5mzoMPohHd/qOWCK8hmHHMMRx7xhl0tbXhGKQdkV+nY+fJJ+GMiwtBdYIQHTqyMin7y1+IFRtLRjURXkMgSRLHnXkms44/npaamkE70PuMRnYuW4rHaAxBhYIwvpmTk8l75BEy+11ILkQnEV5DpNFqOfX732fKggU0VFbiHWQJvSc2lp1LT8ar04WgQkEYnzoTE0j985/ImzYt1KUIYUCE1zAYY2I447LLmDxjBvV79uAfpEeeMymJnacswysumhSEo9YRH0fM3XdTumhRqEsRwoQIr2GKTUzkzCuvJK+khLpduwa9BsyRnEzFKcvwGkSACcJwtcfForrlVmYtWxbqUoQwIsLrKCSlpXHWD39IVl4e9bt3I8sDt+VwJiVRccop4hyYIAxDe2wMnuuuY9HZZ4kl8UIQEV5HKS07m29feSXJGRkHvYjZmZhIxSnLRIAJwhB0xMTg/PGPOfHii1GLbWiEA4jwGgHZkyZx5pVXkpicTP3u3YMGmCshgR3LT8FtMoWgQkGILM3x8div/TFLL71UXMslDEpsiTKCanfu5PWnnqKns5Oc4mJUg3Sc19lslH70McZBOtULggB1SUn4r/ohyy+5RASXcFAivEZY/a5dvP7005jb2sidPHnQAFO73ZT87xPiOjpCUKEghK/daWlorricUy6+GK241EQ4BBFeo6Bhzx5ee+opzC0t5JaUDBpgkt9P0aefkVxfH4IKBSH8bJ4wgdhLvs9yEVzCERDhNUqaqqp47amnaG9sJK+kBNVgJ5wVhbyvviZz586xL1AQwoQsSazPyyP9Oxdxyve+J4JLOCIivEZRc00Nrz/1FC11deROnnzQ+fvM7TvI3bABsRBYiDYerZa1RZOY/N3vcuK556LWaEJdkhAhRHiNso7mZt78+9+p2b6diUVF6A+yXD6pro5Jaz9HPUi3DkEYjywxMXxWMpkF3/sei087bdDpdUE4GBFeY8DS1cXbK1eyY/16svLzMR2k67yxp4fiT1ZhtFrHuEJBGFtNKSlsLC/jpIsvZvYJJ4gLkIUhE+E1Rpx2Ox889xwbVq0iNSuL+IPs+6X2eJj06WckNTWNcYWCMPoUYHt2Ng1Tp/CtSy6hbO7cUJckRCgRXmPI5/Wy6tVXWfvOO8TGxZGSlTX4HRWF7M1byN6yRZwHE8YNn0bDFzk5+GbO4PQf/IC80tJQlyREMBFeY0yWZb784ANWvfoqss9HVkHBQef6ExsamPTZWjRe7xhXKQgjy5qQwKoJWWQtWsRpl15KSmZmqEsSIpwIrxBQFIXdGzfywfPP09HcTE5x8UGXB+utVoo+/YzYzs4xrlIQRkZNbg5fp6Ux6+STWXrRRRhjYkJdkjAOiPAKofbGRt795z+p3LKFzLw8YuLjB7+jLDNx8xYmbNuGJP66hAjh1ev5qqCA9vQ0jj/7bBYuXy4a7AojRoRXiDmsVj76z3/4ZvVqYhMSSMnMPOjKq9i2doo++wy93T7GVQrC0PSmpbEqKxNjTg7Lv/c9SmbPFisKhRElwisM+P1+1n/wAatffx2v2012YeHgHTkIrEbMX/clqbW1Y1ukIBwBWaWiuriY9UYDhdOn862LLyYzLy/UZQnjkAivMLJn82Y+eP55WuvqmFBQgDE29qD3TamuJm/9V2g9njGsUBAOzpqSwpd5ufTo9cw9+WSWnH32Ib+HBeFoiPAKMz0dHXz88sts/fxzTHFxpGVnH3S6ReN0kvfV12IUJoSUX62mbko569VqkidM4KTzz2fqwoVimlAYVSK8wpDf5+Ob1atZ/dprWLu7mThpElq9/qD3T2hsouDLL8W5MGHMWdLT2VRaQpPNRumcOSz77ndJmzAh1GUJUUCEVxhrqq7moxdfpHLLFlInTCAhJeWg91V5vUzctInMnbvEikRh1Pm0WuqmTWODRo3OYGDhqadyzGmnoTMYQl2aECVEeIU5l8PBZ2+9xfoPP8Tn9TKhoOCQu8vGdHZSsO5LYrq6xrBKIVooQMekSWzLy6W1p4e8khJOPO88CqdMEdOEwpgS4RUBFEWhautWVr36KnW7dpGUlkZSevrBPywUhbQ9leRs2ojW5R7bYoVxy5qWRtXMGezq7cVgMjFv6VIWn3qqWJQhhIQIrwjitNlY98EHrP/wQxw2GxPy8w+6xQoEltVnb9lKxs6dqGR5DCsVxhOP0Uj97FnsiYmhu7OTwilTOPG888gXvQmFEBLhFYEaKyv55L//pXLLFmLi4w+5IhECLaZyvtlISl3dGFYpRDq/Rk1raRnVRZNoamzEFBfHolNPZf6yZRhMplCXJ0Q5EV4RyuvxsHH1aj57+22629vJyMkhNiHhkI+J6eggZ+MmElpbx6hKIRLJKhVtJZNpKCmloaMdv89H8YwZHP/tbzOxqCjU5QkCIMIr4nU0N7P2rbfY9uWX+H0+svLyDrviK66tjezNW0SICUFklYqOoiKapk6h1Wqlx2wmu7CQY047jfL581FrNKEuURD6iPAaBxRFoWrbNta+9RbV27djMJlInzjxsB82sW3tTNy8WYRYlFMkic7CQpqmT8Msy7Q1NJCQksL8ZcuYe+KJB935WxBCSYTXOOL1eNj6xRese+89WurqiE9OJiUz86D7he0T2743xFpEiEUTv0ZDx6RJtJaX0aNS0dbQgEarZcr8+Rx7xhmkZWeHukRBOCgRXuOQ3WLhm9Wr+eqjj+hqb+9bWn+4EDOZu8jcWUFKTa1YnTiOeYxG2kpKaCuZjN3vp62hAZVKxaSpU5l/yilMmjpVXLMlhD0RXuNYV3s736xezaY1a+jt7CTxCENM43SSsXsP6bt3o3M6x6haYbQ5EhJoLS+ns7AAl8dDW0MDiqJQWF7O/FNOoWj6dLHflhAxRHhFga72djauWcPG1auHFGKS309KbR0ZOyuINYuOHZFIVqnozplIR3ExvVlZuF0uOpqa8Pl85JeWMn/ZMkpmzRKLMYSII8IriuwLsU1r1tDT0UFCSgpJGRlH9NO2yWwmrbKKlNpatG7RtSPcORIS6CguorOwEJ/BgN1ioaO5GUmSyCkqYt7SpZTNnXvIVmOCEM5EeEWhrvZ2Nn/2GVs++wxzayt6k4m0CROOqKmq5PeT2NhIWlUVCU3NqMS3T9jwazSY8/LoKC7Clp6Ooij0ms10tbVhMJkonDKFWSecwKSpU0VoCRFPhFcUs/X2snPDBjauWUNzTQ2KopCalUVMfPwRnbDXOJ2k1tSQUlMjphVDRFap6MmeQFd+Pt0TJyJrtfh9Prra27F0dRGXmEjZvHnMOOYYcoqLxUIMYdwQ4SXg9Xio3raNzZ99RtW2bThtNhJSUkhMSzvicyE6m52khnqS6xuIa28X27KMIr9aTe+ELLpzc+nOycGv06EoCnaLha62Nvw+H0np6cw49limLlwo9tcSxiURXkIfRVForqlh+5dfsuOrr+hub0elVpOUnk5cYuIR/9SucblIbGwkub6BhJYWVH7/KFc+/nlMJnqysuidmE3PhAnIe6f9vB4P3e3tWHt6MMXGkjt5MtMWLWLStGnExMeHuGpBGD0ivIRBOaxWqrZtY8dXX1FbUYGttxdTbCxJ6elDasoq+XzEtbeT0NpKfEsrMV1dYlR2BPwaNdb0DHonZNE7YQLOxMS+22RZxtLVRU9nJwCpWVlMXbiQklmzyMzLE1ODQlQQ4SUckqIodLa0ULllC9u++ILW+nq8bjcxCQkkpKQMubu42uMhvrWN+NZW4ltbMfb0ID5qA4st7CkpWNPSsGRlYk1PR+m3ClSWZazd3fR2duL3+YhNSqKgvJzyefOYNHXqIbfGEYTxSISXcMT8Ph/1e/ZQs307uzZuxNzaisfpxBATQ0JqKqbY2CH/1K/2eIgxm4kxm4ntDPyqt9tH6R2EBwVwJSRgTU3FlpaKLS0NZ0ICHHDdnd/nw9LdjcVsRvb7iU1MJLekhJJZsygoKyMhNTU0b0AQwoAIL2FYfF4vzTU11O/eza5vvqG9sRGH3Y5eryc2MZHYhIRhL8fWuFx9gWbstWCwBL40Xu8Iv4vR5zEacSYm4ExI3PtrAo6kJPw63YD7KoqC02bD2tOD3WJBUqmIS0wkv7SUohkzyCspITE1VUwLCgIivIQRIMsy7Q0N1O/ezZ7Nm2mpq8PW24vs92MwmYhNSCAmIeGoWw9pnc5AkO0LNJsNncOOzuFE63SG5FyaX6vFYzLhNpnwxMTg2furMyEeZ2LioCHVn8ftxtrdja2nB7/fjyEmhuS0NCZNn87ESZOYOGkScUlJY/RuBCFyiPASRpytp4eWujqaa2qo3r6djqYm7FYryDKGmBiMsbGYYmPR6vUjN4qQZbRuN1qnE63LhdbpQu31oPL6UPt8qHzewK/7fu/3BebvJAllbw2KJBE4ASehqFT4dFr8Wh3+vb/6dFr8Oh1+rRav0YjHZDpsOAWXKOO02bBbLDhtNvx+PxqtlvjkZPJKSsgrLWVCQQFp2dmix6AgHIYIL2FUKYpCb2dnX5g17N6Nua0Nh9WK1+NBUqkwmkx9gabR6cbFtJjf58PldOJ2OHDYbHhcrsB7jYkhPimJnOJisvLzSZswgYzc3CEvfBGEaCfCSxhzDquVzpYWOlta6GhspKGykp6ODhw2G36fDwCVWo3eaERvNGIwGtEZjWE3GlEUBa/Hg9ftxuVw4HI48LhcKIBKkjCYTOhNJjImTiSnuJi07GzSsrMDF3+H2XsRhEgjwksIOUVRsPf2Ym5txdLVRW9XF+bWVjqamrB0deF2OnE5ndDvW1Wr06HR6dBqtWh0OjRaLWqNBpVKhUqtDnwdpmv+YHXIsozs8+H3+/H7fIEvvx+fx4PH7cbrdqPIcmC6EdBqtej0egwxMaRmZpKRl0dSWhoJqakkpaURn5yMdghTi4IgHBkRXkJYczud9JrNWLq6sPX2YrdYsFss9HR2BhY6WCz4PB58Hg9+vx9575dfllFkuW8KUpIkFEWBflOSEoHTXigK+/4RqFQq1Go1ao0GtVqNSqNBrdGgNxpJ3NsyKz4pCVN8PLHx8Zji4ohJSCA+KUk0uxWEMSTCS4hosizjdjhwOhx43e5AkHm9eL1efB4PXo8Hv8+Hb+8ye0mSQJKQ+n1BILR0BgM6gwGtThf4Va9Ht/drRBeXCIJw1ER4CYIgCBFnaCcFBEEQBCEMiPASwlptbS2SJLFp06ZQlyIIQhgR4SUIgiBEHBFegiAIQsQR4SUc0pIlS1ixYgUrVqwgISGB1NRU7rjjDvat83G73dx0001kZ2cTExPDggULWLVqVd/jzWYz3/3ud8nOzsZkMjFt2jSef/75oNeQZZn777+foqIi9Ho9ubm53HvvvUH3qa6u5sQTT8RkMjFjxgy++OKLUX/vgiCELxFewmGtXLkSjUbD+vXrefjhh3nggQd4+umnAVixYgVffPEFL7zwAlu2bOGCCy7g1FNPZc+ePQC4XC7mzJnD22+/zbZt27j66qu55JJLWL9+fd/z33bbbfzhD3/gjjvuYMeOHTz33HNkZGQE1fCrX/2Km266iU2bNjF58mS++93v4tvbjUMQhCikCMIhnHDCCUpZWZkiy3LfsVtuuUUpKytT6urqFLVarTQ1NQU95uSTT1Zuu+22gz7n6aefrvz85z9XFEVRLBaLotfrlaeeemrQ+9bU1CiA8vTTT/cd2759uwIoFRUVR/PWBEGIYJpQh6cQ/hYuXBh0ge6iRYv485//zNatW/H7/UyePDno/m63m5SUFAD8fj+/+93v+M9//kNTUxMejwe3241pbyPaiooK3G43J5988iFrmD59et//Z2VlAdDe3k5paemIvEdBECKLCC9h2Gw2G2q1mg0bNgxoNBsbGwvAH//4Rx5++GEeeughpk2bRkxMDDfeeCMejwcA4xFuX6/t13ppX5DKsjwSb0MQhAgkwks4rC+//DLo9+vWraO4uJhZs2bh9/tpb2/nuOOOG/Sxa9eu5ayzzuL73/8+EAic3bt3U15eDkBxcTFGo5GPP/6YH/7wh6P7RgRBGDfEgg3hsOrr6/nZz37Grl27eP755/nLX/7CDTfcwOTJk7n44ou59NJL+e9//0tNTQ3r16/n97//PW+//TYQCKcPP/yQzz//nIqKCq655hra2tr6nttgMHDLLbdw88038+yzz1JVVcW6dev429/+Fqq3KwhCBBAjL+GwLr30UpxOJ/Pnz0etVnPDDTdw9dVXA/CPf/yDe+65h5///Oc0NTWRmprKwoULOeOMMwC4/fbbqa6uZvny5ZhMJq6++mrOPvtsent7+57/jjvuQKPRcOedd9Lc3ExWVhY/+tGPQvJeBUGIDKIxr3BIS5YsYebMmTz00EOhLkUQBKGPmDYUBEEQIo4IL0EQBCHiiGlDQRAEIeKIkZcgCIIQcUR4CYIgCBFHhJcgCIIQcUR4CYIgCBFHhJcgCIIQcUR4CYIgCBFHhJcgCIIQcUR4CYIgCBFHhJcgCIIQcUR4CYIgCBHn/wHjJ3j8oOOgWgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y=np.array([10,24,34,77])\n",
    "mylabels=['apple','mango','banana','peach']\n",
    "mylllabels=[0.2,.1,0.1,0.1]\n",
    "plt.pie(y ,labels= mylabels,explode=mylllabels,shadow=1,autopct='%1.1f%%')\n",
    "plt.legend(title='fruits')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "joyta\n"
     ]
    }
   ],
   "source": [
    "print('joyta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}